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Duplicate from parler-tts/parler-tts-large-v1
Browse filesCo-authored-by: Yoach Lacombe <ylacombe@users.noreply.huggingface.co>
- .gitattributes +35 -0
- README.md +147 -0
- config.json +282 -0
- generation_config.json +11 -0
- model-00001-of-00002.safetensors +3 -0
- model-00002-of-00002.safetensors +3 -0
- model.safetensors.index.json +951 -0
- preprocessor_config.json +10 -0
- special_tokens_map.json +125 -0
- spiece.model +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +939 -0
.gitattributes
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README.md
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---
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library_name: transformers
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tags:
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- text-to-speech
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- annotation
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license: apache-2.0
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language:
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- en
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pipeline_tag: text-to-speech
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inference: false
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datasets:
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- parler-tts/mls_eng
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- parler-tts/libritts_r_filtered
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- parler-tts/libritts-r-filtered-speaker-descriptions
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- parler-tts/mls-eng-speaker-descriptions
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---
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<img src="https://huggingface.co/datasets/parler-tts/images/resolve/main/thumbnail.png" alt="Parler Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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# Parler-TTS Large v1
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<a target="_blank" href="https://huggingface.co/spaces/parler-tts/parler_tts">
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<img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm.svg" alt="Open in HuggingFace"/>
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</a>
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**Parler-TTS Large v1** is a 2.2B-parameters text-to-speech (TTS) model, trained on 45K hours of audio data, that can generate high-quality, natural sounding speech with features that can be controlled using a simple text prompt (e.g. gender, background noise, speaking rate, pitch and reverberation).
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With [Parler-TTS Mini v1](https://huggingface.co/parler-tts/parler-tts-mini-v1), this is the second set of models published as part of the [Parler-TTS](https://github.com/huggingface/parler-tts) project, which aims to provide the community with TTS training resources and dataset pre-processing code.
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## 📖 Quick Index
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* [👨💻 Installation](#👨💻-installation)
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* [🎲 Using a random voice](#🎲-random-voice)
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* [🎯 Using a specific speaker](#🎯-using-a-specific-speaker)
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* [Motivation](#motivation)
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* [Optimizing inference](https://github.com/huggingface/parler-tts/blob/main/INFERENCE.md)
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## 🛠️ Usage
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### 👨💻 Installation
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Using Parler-TTS is as simple as "bonjour". Simply install the library once:
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```sh
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pip install git+https://github.com/huggingface/parler-tts.git
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```
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### 🎲 Random voice
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**Parler-TTS** has been trained to generate speech with features that can be controlled with a simple text prompt, for example:
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```py
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import torch
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from parler_tts import ParlerTTSForConditionalGeneration
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from transformers import AutoTokenizer
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import soundfile as sf
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device = "cuda:0" if torch.cuda.is_available() else "cpu"
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model = ParlerTTSForConditionalGeneration.from_pretrained("parler-tts/parler-tts-large-v1").to(device)
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tokenizer = AutoTokenizer.from_pretrained("parler-tts/parler-tts-large-v1")
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prompt = "Hey, how are you doing today?"
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description = "A female speaker delivers a slightly expressive and animated speech with a moderate speed and pitch. The recording is of very high quality, with the speaker's voice sounding clear and very close up."
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input_ids = tokenizer(description, return_tensors="pt").input_ids.to(device)
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prompt_input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(device)
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generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids)
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audio_arr = generation.cpu().numpy().squeeze()
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sf.write("parler_tts_out.wav", audio_arr, model.config.sampling_rate)
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```
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### 🎯 Using a specific speaker
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To ensure speaker consistency across generations, this checkpoint was also trained on 34 speakers, characterized by name (e.g. Jon, Lea, Gary, Jenna, Mike, Laura).
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To take advantage of this, simply adapt your text description to specify which speaker to use: `Jon's voice is monotone yet slightly fast in delivery, with a very close recording that almost has no background noise.`
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```py
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import torch
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from parler_tts import ParlerTTSForConditionalGeneration
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from transformers import AutoTokenizer
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import soundfile as sf
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device = "cuda:0" if torch.cuda.is_available() else "cpu"
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model = ParlerTTSForConditionalGeneration.from_pretrained("parler-tts/parler-tts-large-v1").to(device)
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tokenizer = AutoTokenizer.from_pretrained("parler-tts/parler-tts-large-v1")
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prompt = "Hey, how are you doing today?"
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description = "Jon's voice is monotone yet slightly fast in delivery, with a very close recording that almost has no background noise."
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input_ids = tokenizer(description, return_tensors="pt").input_ids.to(device)
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prompt_input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(device)
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generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids)
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audio_arr = generation.cpu().numpy().squeeze()
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sf.write("parler_tts_out.wav", audio_arr, model.config.sampling_rate)
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```
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**Tips**:
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* We've set up an [inference guide](https://github.com/huggingface/parler-tts/blob/main/INFERENCE.md) to make generation faster. Think SDPA, torch.compile, batching and streaming!
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* Include the term "very clear audio" to generate the highest quality audio, and "very noisy audio" for high levels of background noise
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* Punctuation can be used to control the prosody of the generations, e.g. use commas to add small breaks in speech
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* The remaining speech features (gender, speaking rate, pitch and reverberation) can be controlled directly through the prompt
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## Motivation
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Parler-TTS is a reproduction of work from the paper [Natural language guidance of high-fidelity text-to-speech with synthetic annotations](https://www.text-description-to-speech.com) by Dan Lyth and Simon King, from Stability AI and Edinburgh University respectively.
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Contrarily to other TTS models, Parler-TTS is a **fully open-source** release. All of the datasets, pre-processing, training code and weights are released publicly under permissive license, enabling the community to build on our work and develop their own powerful TTS models.
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Parler-TTS was released alongside:
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* [The Parler-TTS repository](https://github.com/huggingface/parler-tts) - you can train and fine-tuned your own version of the model.
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* [The Data-Speech repository](https://github.com/huggingface/dataspeech) - a suite of utility scripts designed to annotate speech datasets.
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* [The Parler-TTS organization](https://huggingface.co/parler-tts) - where you can find the annotated datasets as well as the future checkpoints.
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## Citation
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If you found this repository useful, please consider citing this work and also the original Stability AI paper:
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```
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@misc{lacombe-etal-2024-parler-tts,
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author = {Yoach Lacombe and Vaibhav Srivastav and Sanchit Gandhi},
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title = {Parler-TTS},
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year = {2024},
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publisher = {GitHub},
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journal = {GitHub repository},
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howpublished = {\url{https://github.com/huggingface/parler-tts}}
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}
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```
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```
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@misc{lyth2024natural,
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title={Natural language guidance of high-fidelity text-to-speech with synthetic annotations},
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author={Dan Lyth and Simon King},
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year={2024},
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eprint={2402.01912},
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archivePrefix={arXiv},
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primaryClass={cs.SD}
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}
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```
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## License
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This model is permissively licensed under the Apache 2.0 license.
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config.json
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model-00001-of-00002.safetensors
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|
| 950 |
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|
| 951 |
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preprocessor_config.json
ADDED
|
@@ -0,0 +1,10 @@
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+
{
|
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+
"chunk_length_s": null,
|
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"feature_extractor_type": "EncodecFeatureExtractor",
|
| 4 |
+
"feature_size": 1,
|
| 5 |
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"overlap": null,
|
| 6 |
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"padding_side": "right",
|
| 7 |
+
"padding_value": 0.0,
|
| 8 |
+
"return_attention_mask": true,
|
| 9 |
+
"sampling_rate": 44100
|
| 10 |
+
}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,125 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"additional_special_tokens": [
|
| 3 |
+
"<extra_id_0>",
|
| 4 |
+
"<extra_id_1>",
|
| 5 |
+
"<extra_id_2>",
|
| 6 |
+
"<extra_id_3>",
|
| 7 |
+
"<extra_id_4>",
|
| 8 |
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"<extra_id_5>",
|
| 9 |
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"<extra_id_6>",
|
| 10 |
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"<extra_id_7>",
|
| 11 |
+
"<extra_id_8>",
|
| 12 |
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"<extra_id_9>",
|
| 13 |
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"<extra_id_10>",
|
| 14 |
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"<extra_id_11>",
|
| 15 |
+
"<extra_id_12>",
|
| 16 |
+
"<extra_id_13>",
|
| 17 |
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"<extra_id_14>",
|
| 18 |
+
"<extra_id_15>",
|
| 19 |
+
"<extra_id_16>",
|
| 20 |
+
"<extra_id_17>",
|
| 21 |
+
"<extra_id_18>",
|
| 22 |
+
"<extra_id_19>",
|
| 23 |
+
"<extra_id_20>",
|
| 24 |
+
"<extra_id_21>",
|
| 25 |
+
"<extra_id_22>",
|
| 26 |
+
"<extra_id_23>",
|
| 27 |
+
"<extra_id_24>",
|
| 28 |
+
"<extra_id_25>",
|
| 29 |
+
"<extra_id_26>",
|
| 30 |
+
"<extra_id_27>",
|
| 31 |
+
"<extra_id_28>",
|
| 32 |
+
"<extra_id_29>",
|
| 33 |
+
"<extra_id_30>",
|
| 34 |
+
"<extra_id_31>",
|
| 35 |
+
"<extra_id_32>",
|
| 36 |
+
"<extra_id_33>",
|
| 37 |
+
"<extra_id_34>",
|
| 38 |
+
"<extra_id_35>",
|
| 39 |
+
"<extra_id_36>",
|
| 40 |
+
"<extra_id_37>",
|
| 41 |
+
"<extra_id_38>",
|
| 42 |
+
"<extra_id_39>",
|
| 43 |
+
"<extra_id_40>",
|
| 44 |
+
"<extra_id_41>",
|
| 45 |
+
"<extra_id_42>",
|
| 46 |
+
"<extra_id_43>",
|
| 47 |
+
"<extra_id_44>",
|
| 48 |
+
"<extra_id_45>",
|
| 49 |
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"<extra_id_46>",
|
| 50 |
+
"<extra_id_47>",
|
| 51 |
+
"<extra_id_48>",
|
| 52 |
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"<extra_id_49>",
|
| 53 |
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"<extra_id_50>",
|
| 54 |
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"<extra_id_51>",
|
| 55 |
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"<extra_id_52>",
|
| 56 |
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"<extra_id_53>",
|
| 57 |
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|
| 58 |
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"<extra_id_55>",
|
| 59 |
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|
| 60 |
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|
| 61 |
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"<extra_id_58>",
|
| 62 |
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|
| 63 |
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"<extra_id_60>",
|
| 64 |
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"<extra_id_61>",
|
| 65 |
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"<extra_id_62>",
|
| 66 |
+
"<extra_id_63>",
|
| 67 |
+
"<extra_id_64>",
|
| 68 |
+
"<extra_id_65>",
|
| 69 |
+
"<extra_id_66>",
|
| 70 |
+
"<extra_id_67>",
|
| 71 |
+
"<extra_id_68>",
|
| 72 |
+
"<extra_id_69>",
|
| 73 |
+
"<extra_id_70>",
|
| 74 |
+
"<extra_id_71>",
|
| 75 |
+
"<extra_id_72>",
|
| 76 |
+
"<extra_id_73>",
|
| 77 |
+
"<extra_id_74>",
|
| 78 |
+
"<extra_id_75>",
|
| 79 |
+
"<extra_id_76>",
|
| 80 |
+
"<extra_id_77>",
|
| 81 |
+
"<extra_id_78>",
|
| 82 |
+
"<extra_id_79>",
|
| 83 |
+
"<extra_id_80>",
|
| 84 |
+
"<extra_id_81>",
|
| 85 |
+
"<extra_id_82>",
|
| 86 |
+
"<extra_id_83>",
|
| 87 |
+
"<extra_id_84>",
|
| 88 |
+
"<extra_id_85>",
|
| 89 |
+
"<extra_id_86>",
|
| 90 |
+
"<extra_id_87>",
|
| 91 |
+
"<extra_id_88>",
|
| 92 |
+
"<extra_id_89>",
|
| 93 |
+
"<extra_id_90>",
|
| 94 |
+
"<extra_id_91>",
|
| 95 |
+
"<extra_id_92>",
|
| 96 |
+
"<extra_id_93>",
|
| 97 |
+
"<extra_id_94>",
|
| 98 |
+
"<extra_id_95>",
|
| 99 |
+
"<extra_id_96>",
|
| 100 |
+
"<extra_id_97>",
|
| 101 |
+
"<extra_id_98>",
|
| 102 |
+
"<extra_id_99>"
|
| 103 |
+
],
|
| 104 |
+
"eos_token": {
|
| 105 |
+
"content": "</s>",
|
| 106 |
+
"lstrip": false,
|
| 107 |
+
"normalized": false,
|
| 108 |
+
"rstrip": false,
|
| 109 |
+
"single_word": false
|
| 110 |
+
},
|
| 111 |
+
"pad_token": {
|
| 112 |
+
"content": "<pad>",
|
| 113 |
+
"lstrip": false,
|
| 114 |
+
"normalized": false,
|
| 115 |
+
"rstrip": false,
|
| 116 |
+
"single_word": false
|
| 117 |
+
},
|
| 118 |
+
"unk_token": {
|
| 119 |
+
"content": "<unk>",
|
| 120 |
+
"lstrip": false,
|
| 121 |
+
"normalized": false,
|
| 122 |
+
"rstrip": false,
|
| 123 |
+
"single_word": false
|
| 124 |
+
}
|
| 125 |
+
}
|
spiece.model
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d60acb128cf7b7f2536e8f38a5b18a05535c9e14c7a355904270e15b0945ea86
|
| 3 |
+
size 791656
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,939 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
|
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|
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|
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|
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|
|
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| 1 |
+
{
|
| 2 |
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"added_tokens_decoder": {
|
| 3 |
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"0": {
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| 4 |
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| 5 |
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| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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"special": true
|
| 10 |
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},
|
| 11 |
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"1": {
|
| 12 |
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"content": "</s>",
|
| 13 |
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"lstrip": false,
|
| 14 |
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"normalized": false,
|
| 15 |
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"rstrip": false,
|
| 16 |
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|
| 17 |
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"special": true
|
| 18 |
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},
|
| 19 |
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"2": {
|
| 20 |
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|
| 21 |
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| 22 |
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|
| 23 |
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| 24 |
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|
| 25 |
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"special": true
|
| 26 |
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},
|
| 27 |
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"32000": {
|
| 28 |
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|
| 29 |
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| 30 |
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| 31 |
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|
| 32 |
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| 33 |
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|
| 34 |
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| 35 |
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|
| 36 |
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|
| 37 |
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| 38 |
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| 39 |
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| 40 |
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| 41 |
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| 42 |
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| 43 |
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| 44 |
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|
| 45 |
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| 46 |
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| 47 |
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| 48 |
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|
| 49 |
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| 50 |
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| 51 |
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| 52 |
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|
| 53 |
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| 54 |
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| 55 |
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| 56 |
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| 57 |
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| 58 |
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| 59 |
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| 60 |
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| 61 |
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| 62 |
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| 63 |
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| 64 |
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| 65 |
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| 66 |
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| 67 |
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|
| 68 |
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|
| 69 |
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| 70 |
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| 71 |
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|
| 72 |
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| 73 |
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|
| 74 |
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| 75 |
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|
| 76 |
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"content": "<extra_id_93>",
|
| 77 |
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| 78 |
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| 79 |
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| 80 |
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| 81 |
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|
| 82 |
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| 83 |
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|
| 84 |
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|
| 85 |
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| 86 |
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| 87 |
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| 88 |
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| 89 |
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| 90 |
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| 91 |
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| 92 |
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| 93 |
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|
| 94 |
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| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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| 99 |
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|
| 100 |
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"content": "<extra_id_90>",
|
| 101 |
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|
| 102 |
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| 103 |
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|
| 104 |
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|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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| 111 |
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| 112 |
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| 113 |
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|
| 114 |
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| 115 |
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|
| 116 |
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|
| 117 |
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| 118 |
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| 119 |
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| 120 |
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| 121 |
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|
| 122 |
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|
| 123 |
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| 124 |
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|
| 125 |
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|
| 126 |
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| 127 |
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| 128 |
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|
| 129 |
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| 130 |
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| 131 |
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| 132 |
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| 133 |
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| 134 |
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| 135 |
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| 136 |
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|
| 137 |
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|
| 138 |
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| 139 |
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|
| 140 |
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|
| 141 |
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|
| 142 |
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| 143 |
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|
| 144 |
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| 145 |
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| 146 |
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| 147 |
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|
| 148 |
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"content": "<extra_id_84>",
|
| 149 |
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| 150 |
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| 151 |
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| 152 |
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| 153 |
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| 154 |
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|
| 155 |
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|
| 156 |
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"content": "<extra_id_83>",
|
| 157 |
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|
| 158 |
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| 159 |
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| 160 |
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| 161 |
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| 162 |
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| 163 |
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|
| 164 |
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|
| 165 |
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|
| 166 |
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| 167 |
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| 168 |
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| 169 |
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| 170 |
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| 171 |
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| 172 |
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| 173 |
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| 174 |
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| 175 |
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| 176 |
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| 177 |
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| 178 |
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| 179 |
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|
| 180 |
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| 181 |
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| 182 |
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| 183 |
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| 184 |
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| 185 |
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| 186 |
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| 187 |
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|
| 188 |
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| 189 |
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| 190 |
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| 191 |
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| 192 |
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| 193 |
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|
| 194 |
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| 195 |
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|
| 196 |
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|
| 197 |
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| 198 |
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| 199 |
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| 200 |
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| 201 |
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| 202 |
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| 203 |
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|
| 204 |
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|
| 205 |
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| 206 |
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| 207 |
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| 208 |
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| 209 |
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| 210 |
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| 211 |
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|
| 212 |
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| 213 |
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| 214 |
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| 215 |
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| 216 |
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| 217 |
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| 218 |
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| 219 |
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| 220 |
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| 221 |
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| 222 |
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| 223 |
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| 224 |
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| 225 |
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| 226 |
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| 227 |
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| 228 |
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| 230 |
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| 231 |
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| 681 |
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| 682 |
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| 689 |
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| 690 |
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| 697 |
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| 698 |
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| 700 |
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| 724 |
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| 929 |
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| 930 |
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| 931 |
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| 939 |
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}
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