Commit
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09e5b0b
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Parent(s):
Duplicate from llava-hf/llava-1.5-7b-hf
Browse filesCo-authored-by: Younes Belkada <ybelkada@users.noreply.huggingface.co>
- .gitattributes +35 -0
- README.md +121 -0
- added_tokens.json +4 -0
- config.json +38 -0
- generation_config.json +7 -0
- model-00001-of-00003.safetensors +3 -0
- model-00002-of-00003.safetensors +3 -0
- model-00003-of-00003.safetensors +3 -0
- model.safetensors.index.json +693 -0
- preprocessor_config.json +29 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +59 -0
.gitattributes
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README.md
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---
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language:
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- en
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pipeline_tag: image-to-text
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inference: false
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arxiv: 2304.08485
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datasets:
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- liuhaotian/LLaVA-Instruct-150K
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---
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# LLaVA Model Card
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Below is the model card of Llava model 7b, which is copied from the original Llava model card that you can find [here](https://huggingface.co/liuhaotian/llava-v1.5-13b).
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Check out also the Google Colab demo to run Llava on a free-tier Google Colab instance: [](https://colab.research.google.com/drive/1qsl6cd2c8gGtEW1xV5io7S8NHh-Cp1TV?usp=sharing)
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Or check out our Spaces demo! [](https://huggingface.co/spaces/llava-hf/llava-4bit)
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## Model details
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**Model type:**
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LLaVA is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data.
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It is an auto-regressive language model, based on the transformer architecture.
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**Model date:**
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LLaVA-v1.5-7B was trained in September 2023.
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**Paper or resources for more information:**
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https://llava-vl.github.io/
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## How to use the model
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First, make sure to have `transformers >= 4.35.3`.
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The model supports multi-image and multi-prompt generation. Meaning that you can pass multiple images in your prompt. Make sure also to follow the correct prompt template (`USER: xxx\nASSISTANT:`) and add the token `<image>` to the location where you want to query images:
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### Using `pipeline`:
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Below we used [`"llava-hf/llava-1.5-7b-hf"`](https://huggingface.co/llava-hf/llava-1.5-7b-hf) checkpoint.
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```python
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from transformers import pipeline
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from PIL import Image
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import requests
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model_id = "llava-hf/llava-1.5-7b-hf"
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pipe = pipeline("image-to-text", model=model_id)
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url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg"
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image = Image.open(requests.get(url, stream=True).raw)
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prompt = "USER: <image>\nWhat does the label 15 represent? (1) lava (2) core (3) tunnel (4) ash cloud\nASSISTANT:"
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outputs = pipe(image, prompt=prompt, generate_kwargs={"max_new_tokens": 200})
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print(outputs)
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>>> {"generated_text": "\nUSER: What does the label 15 represent? (1) lava (2) core (3) tunnel (4) ash cloud\nASSISTANT: Lava"}
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```
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### Using pure `transformers`:
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Below is an example script to run generation in `float16` precision on a GPU device:
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```python
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import requests
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from PIL import Image
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import torch
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from transformers import AutoProcessor, LlavaForConditionalGeneration
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model_id = "llava-hf/llava-1.5-7b-hf"
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prompt = "USER: <image>\nWhat are these?\nASSISTANT:"
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image_file = "http://images.cocodataset.org/val2017/000000039769.jpg"
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model = LlavaForConditionalGeneration.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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low_cpu_mem_usage=True,
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).to(0)
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processor = AutoProcessor.from_pretrained(model_id)
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raw_image = Image.open(requests.get(image_file, stream=True).raw)
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inputs = processor(prompt, raw_image, return_tensors='pt').to(0, torch.float16)
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output = model.generate(**inputs, max_new_tokens=200, do_sample=False)
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print(processor.decode(output[0][2:], skip_special_tokens=True))
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```
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### Model optimization
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#### 4-bit quantization through `bitsandbytes` library
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First make sure to install `bitsandbytes`, `pip install bitsandbytes` and make sure to have access to a CUDA compatible GPU device. Simply change the snippet above with:
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```diff
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model = LlavaForConditionalGeneration.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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low_cpu_mem_usage=True,
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+ load_in_4bit=True
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)
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```
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#### Use Flash-Attention 2 to further speed-up generation
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First make sure to install `flash-attn`. Refer to the [original repository of Flash Attention](https://github.com/Dao-AILab/flash-attention) regarding that package installation. Simply change the snippet above with:
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```diff
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model = LlavaForConditionalGeneration.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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low_cpu_mem_usage=True,
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+ use_flash_attention_2=True
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).to(0)
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```
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## License
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Llama 2 is licensed under the LLAMA 2 Community License,
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Copyright (c) Meta Platforms, Inc. All Rights Reserved.
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added_tokens.json
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{
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"<image>": 32000,
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"<pad>": 32001
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}
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config.json
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{
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"architectures": [
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"LlavaForConditionalGeneration"
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],
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"ignore_index": -100,
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"image_token_index": 32000,
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"model_type": "llava",
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"pad_token_id": 32001,
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"projector_hidden_act": "gelu",
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"text_config": {
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"_name_or_path": "lmsys/vicuna-7b-v1.5",
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"architectures": [
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"LlamaForCausalLM"
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],
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"max_position_embeddings": 4096,
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"model_type": "llama",
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"rms_norm_eps": 1e-05,
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"torch_dtype": "float16",
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"vocab_size": 32064
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},
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.36.0.dev0",
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"vision_config": {
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"hidden_size": 1024,
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"image_size": 336,
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"intermediate_size": 4096,
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"model_type": "clip_vision_model",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"patch_size": 14,
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"projection_dim": 768,
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"vocab_size": 32000
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},
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"vision_feature_layer": -2,
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"vision_feature_select_strategy": "default",
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"vocab_size": 32064
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": 32001,
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"transformers_version": "4.36.0.dev0"
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}
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model-00001-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c11dbf016ee7d35ee130c19b67e20eb04873996006f424b7bcbd453b6517ee66
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size 4992930200
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model-00002-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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model-00003-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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size 4176137408
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model.safetensors.index.json
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"vision_tower.vision_model.encoder.layers.9.self_attn.q_proj.weight": "model-00001-of-00003.safetensors",
|
| 686 |
+
"vision_tower.vision_model.encoder.layers.9.self_attn.v_proj.bias": "model-00001-of-00003.safetensors",
|
| 687 |
+
"vision_tower.vision_model.encoder.layers.9.self_attn.v_proj.weight": "model-00001-of-00003.safetensors",
|
| 688 |
+
"vision_tower.vision_model.post_layernorm.bias": "model-00001-of-00003.safetensors",
|
| 689 |
+
"vision_tower.vision_model.post_layernorm.weight": "model-00001-of-00003.safetensors",
|
| 690 |
+
"vision_tower.vision_model.pre_layrnorm.bias": "model-00001-of-00003.safetensors",
|
| 691 |
+
"vision_tower.vision_model.pre_layrnorm.weight": "model-00001-of-00003.safetensors"
|
| 692 |
+
}
|
| 693 |
+
}
|
preprocessor_config.json
ADDED
|
@@ -0,0 +1,29 @@
|
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|
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|
|
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|
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|
|
|
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|
| 1 |
+
{
|
| 2 |
+
"crop_size": {
|
| 3 |
+
"height": 336,
|
| 4 |
+
"width": 336
|
| 5 |
+
},
|
| 6 |
+
"do_center_crop": true,
|
| 7 |
+
"do_convert_rgb": true,
|
| 8 |
+
"do_normalize": true,
|
| 9 |
+
"do_rescale": true,
|
| 10 |
+
"do_resize": true,
|
| 11 |
+
"feature_extractor_type": "CLIPFeatureExtractor",
|
| 12 |
+
"image_mean": [
|
| 13 |
+
0.48145466,
|
| 14 |
+
0.4578275,
|
| 15 |
+
0.40821073
|
| 16 |
+
],
|
| 17 |
+
"image_processor_type": "CLIPImageProcessor",
|
| 18 |
+
"image_std": [
|
| 19 |
+
0.26862954,
|
| 20 |
+
0.26130258,
|
| 21 |
+
0.27577711
|
| 22 |
+
],
|
| 23 |
+
"processor_class": "LlavaProcessor",
|
| 24 |
+
"resample": 3,
|
| 25 |
+
"rescale_factor": 0.00392156862745098,
|
| 26 |
+
"size": {
|
| 27 |
+
"shortest_edge": 336
|
| 28 |
+
}
|
| 29 |
+
}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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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 |
+
"bos_token": {
|
| 3 |
+
"content": "<s>",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"eos_token": {
|
| 10 |
+
"content": "</s>",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"pad_token": "<pad>",
|
| 17 |
+
"unk_token": {
|
| 18 |
+
"content": "<unk>",
|
| 19 |
+
"lstrip": false,
|
| 20 |
+
"normalized": false,
|
| 21 |
+
"rstrip": false,
|
| 22 |
+
"single_word": false
|
| 23 |
+
}
|
| 24 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer.model
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
|
| 3 |
+
size 499723
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,59 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": true,
|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"0": {
|
| 6 |
+
"content": "<unk>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"1": {
|
| 14 |
+
"content": "<s>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"2": {
|
| 22 |
+
"content": "</s>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": false,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": true
|
| 28 |
+
},
|
| 29 |
+
"32000": {
|
| 30 |
+
"content": "<image>",
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"normalized": false,
|
| 33 |
+
"rstrip": false,
|
| 34 |
+
"single_word": false,
|
| 35 |
+
"special": true
|
| 36 |
+
},
|
| 37 |
+
"32001": {
|
| 38 |
+
"content": "<pad>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": false,
|
| 41 |
+
"rstrip": false,
|
| 42 |
+
"single_word": false,
|
| 43 |
+
"special": true
|
| 44 |
+
}
|
| 45 |
+
},
|
| 46 |
+
"bos_token": "<s>",
|
| 47 |
+
"clean_up_tokenization_spaces": false,
|
| 48 |
+
"eos_token": "</s>",
|
| 49 |
+
"legacy": false,
|
| 50 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 51 |
+
"pad_token": "<pad>",
|
| 52 |
+
"padding_side": "left",
|
| 53 |
+
"processor_class": "LlavaProcessor",
|
| 54 |
+
"sp_model_kwargs": {},
|
| 55 |
+
"tokenizer_class": "LlamaTokenizer",
|
| 56 |
+
"trust_remote_code": false,
|
| 57 |
+
"unk_token": "<unk>",
|
| 58 |
+
"use_default_system_prompt": false
|
| 59 |
+
}
|