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Browse files- LICENSE +21 -0
- README.md +61 -0
- generation_config.json +6 -0
- pytorch_model-00001-of-00014.bin +3 -0
- pytorch_model-00002-of-00014.bin +3 -0
- pytorch_model-00003-of-00014.bin +3 -0
- pytorch_model-00004-of-00014.bin +3 -0
- pytorch_model-00005-of-00014.bin +3 -0
- pytorch_model-00006-of-00014.bin +3 -0
- pytorch_model-00007-of-00014.bin +3 -0
- pytorch_model-00008-of-00014.bin +3 -0
- pytorch_model-00009-of-00014.bin +3 -0
- pytorch_model-00010-of-00014.bin +3 -0
- pytorch_model-00011-of-00014.bin +3 -0
- pytorch_model-00012-of-00014.bin +3 -0
- pytorch_model-00013-of-00014.bin +3 -0
- pytorch_model-00014-of-00014.bin +3 -0
- pytorch_model.bin.index.json +0 -0
- spiece.model +3 -0
- tokenizer_config.json +15 -0
LICENSE
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MIT License
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Copyright (c) 2024 SB Intuitions
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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README.md
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---
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license: mit
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---
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---
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license: mit
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language:
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- ja
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---
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# Sarashina1-65B
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This repository provides Japanese language models trained by [SB Intuitions](https://www.sbintuitions.co.jp/).
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## How to use
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```
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, set_seed
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model = AutoModelForCausalLM.from_pretrained("sbintuitions/sarashina1-65b", torch_dtype=torch.float16)
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tokenizer = AutoTokenizer.from_pretrained("sbintuitions/sarashina1-65b", use_fast=False)
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generator = pipeline("text-generation", model=model, tokenizer=tokenizer, device_map="auto")
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set_seed(123)
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text = generator(
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"おはようございます、今日の天気は",
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max_length=30,
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do_sample=True,
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pad_token_id=tokenizer.pad_token_id,
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num_return_sequences=3,
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)
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for t in text:
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print(t)
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```
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## Configuration
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| Parameters | Vocab size | Trainning tokens | Architecture | Position type | Layers | Hidden dim | Attention heads |
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| :-----: | :-----------: | :-------------: | :----------- | :-----------: | :----: | :--------: | :-------------: |
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| [7B](https://huggingface.co/sbintuitions/sarashina1-7b) | 51200 | 1.0T | GPTNeoX | RoPE | 32 | 4096 | 32 |
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| [13B](https://huggingface.co/sbintuitions/sarashina1-13b) | 51200 | 1.0T | GPTNeoX | RoPE | 40 | 5120 | 40 |
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| [65B](https://huggingface.co/sbintuitions/sarashina1-65b) | 51200 | 800B | GPTNeoX | RoPE | 80 | 8192 | 64 |
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## Training Corpus
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We used a Japanese portion of the [Common Crawl corpus](https://commoncrawl.org/), which is the largest Web corpus, as our training dataset.
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To clean the training corpus, we used [CCNet](https://github.com/facebookresearch/cc_net) and [HojiChar](https://github.com/HojiChar/HojiChar).
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After cleaning, our corpus contains about 550B tokens.
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## Tokenization
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We use a [sentencepiece](https://github.com/google/sentencepiece) tokenizer with a unigram language model and byte-fallback.
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We do not apply pre-tokenization with Japanese tokenizer.
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Thus, a user may directly feed raw sentences into the tokenizer.
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## Ethical Considerations and Limitations
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Sarashina1 has not been tuned to follow an instruction yet.
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Therefore, sarashina1 might generate some meaningless sequences, some inaccurate instances or biased/objectionable outputs.
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Before using sarashina1, we would like developers to tune models based on human preferences and safety considerations.
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## License
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[MIT License](https://huggingface.co/sbintuitions/sarashina1-65b/blob/main/LICENSE)
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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": 2,
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"eos_token_id": 2,
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"transformers_version": "4.30.2"
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}
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pytorch_model-00001-of-00014.bin
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spiece.model
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tokenizer_config.json
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{
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"extra_ids": 0,
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"do_lower_case": false,
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"keep_accents": true,
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"bos_token": "<s>",
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"eos_token": "</s>",
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"unk_token": "<unk>",
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"pad_token": "<pad>",
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"mask_token": "<mask>",
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"cls_token": "<cls>",
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"sep_token": "<sep>",
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"sp_model_kwargs": {},
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"special_tokens_map_file": null,
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"tokenizer_class": "T5Tokenizer"
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}
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