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--- |
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license: mit |
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language: ja |
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datasets: |
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- kunishou/databricks-dolly-15k-ja |
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- wikipedia |
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- cc100 |
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- mc4 |
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tags: |
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- japanese |
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- causal-lm |
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- open-calm |
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inference: false |
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--- |
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# OpenCALM-LARGE |
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## Model Description |
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OpenCALM is a suite of decoder-only language models pre-trained on Japanese datasets, developed by CyberAgent, Inc. |
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このモデルはpeftを用いてopen-calm-largeをLoRAファインチューニングしたものです。 |
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## Usage |
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pytorchおよびtransformers, peftをインストールして下記コードを実行してください |
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（pip install torch, transformers, peft） |
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and please execute this code. |
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下記コードに関してはnpakaさんの記事(https://note.com/npaka/n/na5b8e6f749ce)の記事を参考にさせて頂きました。 |
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感謝致します。 |
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```python |
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import torch |
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from peft import PeftModel, PeftConfig |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_name = "cyberagent/open-calm-large" |
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lora_weights = "Mizuiro-sakura/open-calm-large-finetuned-databricks-dolly" |
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# モデルの準備 |
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model = AutoModelForCausalLM.from_pretrained( |
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model_name |
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) |
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# トークンナイザーの準備 |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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# LoRAモデルの準備 |
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model = PeftModel.from_pretrained( |
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model, |
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lora_weights, |
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adapter_name=lora_weights |
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) |
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# 評価モード |
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model.eval() |
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# プロンプトテンプレートの準備 |
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def generate_prompt(data_point): |
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if data_point["input"]: |
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return f"""Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. |
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### Instruction: |
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{data_point["instruction"]} |
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### Input: |
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{data_point["input"]} |
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### Response:""" |
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else: |
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return f"""Below is an instruction that describes a task. Write a response that appropriately completes the request. |
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### Instruction: |
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{data_point["instruction"]} |
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### Response:""" |
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# テキスト生成関数の定義 |
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def generate(instruction,input=None,maxTokens=256): |
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# 推論 |
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prompt = generate_prompt({'instruction':instruction,'input':input}) |
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input_ids = tokenizer(prompt, return_tensors="pt", truncation=True).input_ids |
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outputs = model.generate( |
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input_ids=input_ids, |
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max_new_tokens=maxTokens, |
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do_sample=True, |
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temperature=0.7, |
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top_p=0.75, |
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top_k=40, |
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no_repeat_ngram_size=2, |
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) |
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outputs = outputs[0].tolist() |
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# EOSトークンにヒットしたらデコード完了 |
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if tokenizer.eos_token_id in outputs: |
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eos_index = outputs.index(tokenizer.eos_token_id) |
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else: |
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eos_index = len(outputs) |
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decoded = tokenizer.decode(outputs[:eos_index]) |
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# レスポンス内容のみ抽出 |
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sentinel = "### Response:" |
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sentinelLoc = decoded.find(sentinel) |
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if sentinelLoc >= 0: |
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print(decoded[sentinelLoc+len(sentinel):]) |
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else: |
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print('Warning: Expected prompt template to be emitted. Ignoring output.') |
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generate("自然言語処理とは？") |
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``` |
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## Model Details |
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|Model|Params|Layers|Dim|Heads|Dev ppl| |
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|:---:|:---: |:---:|:---:|:---:|:---:| |
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|[cyberagent/open-calm-small](https://huggingface.co/cyberagent/open-calm-small)|160M|12|768|12|19.7| |
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|[cyberagent/open-calm-medium](https://huggingface.co/cyberagent/open-calm-medium)|400M|24|1024|16|13.8| |
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|[cyberagent/open-calm-large](https://huggingface.co/cyberagent/open-calm-large)|830M|24|1536|16|11.3| |
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|[cyberagent/open-calm-1b](https://huggingface.co/cyberagent/open-calm-1b)|1.4B|24|2048|16|10.3| |
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|[cyberagent/open-calm-3b](https://huggingface.co/cyberagent/open-calm-3b)|2.7B|32|2560|32|9.7| |
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|[cyberagent/open-calm-7b](https://huggingface.co/cyberagent/open-calm-7b)|6.8B|32|4096|32|8.2| |
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* **Developed by**: [CyberAgent, Inc.](https://www.cyberagent.co.jp/) |
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* **Model type**: Transformer-based Language Model |
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* **Language**: Japanese |
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* **Library**: [GPT-NeoX](https://github.com/EleutherAI/gpt-neox) |
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* **License**: OpenCALM is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License ([CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)). When using this model, please provide appropriate credit to CyberAgent, Inc. |
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* Example (en): This model is a fine-tuned version of OpenCALM-XX developed by CyberAgent, Inc. The original model is released under the CC BY-SA 4.0 license, and this model is also released under the same CC BY-SA 4.0 license. For more information, please visit: https://creativecommons.org/licenses/by-sa/4.0/ |
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* Example (ja): 本モデルは、株式会社サイバーエージェントによるOpenCALM-XXをファインチューニングしたものです。元のモデルはCC BY-SA 4.0ライセンスのもとで公開されており、本モデルも同じくCC BY-SA 4.0ライセンスで公開します。詳しくはこちらをご覧ください: https://creativecommons.org/licenses/by-sa/4.0/ |
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## Training Dataset |
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* Wikipedia (ja) |
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* Common Crawl (ja) |
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## Author |
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[Ryosuke Ishigami](https://huggingface.co/rishigami) |
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## Citations |
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```bibtext |
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@software{gpt-neox-library, |
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title = {{GPT-NeoX: Large Scale Autoregressive Language Modeling in PyTorch}}, |
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author = {Andonian, Alex and Anthony, Quentin and Biderman, Stella and Black, Sid and Gali, Preetham and Gao, Leo and Hallahan, Eric and Levy-Kramer, Josh and Leahy, Connor and Nestler, Lucas and Parker, Kip and Pieler, Michael and Purohit, Shivanshu and Songz, Tri and Phil, Wang and Weinbach, Samuel}, |
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url = {https://www.github.com/eleutherai/gpt-neox}, |
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doi = {10.5281/zenodo.5879544}, |
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month = {8}, |
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year = {2021}, |
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version = {0.0.1}, |
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} |
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``` |
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