69 lines
1.9 KiB
Markdown
69 lines
1.9 KiB
Markdown
---
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license: apache-2.0
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language:
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- ja
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- en
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tags:
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- japanese
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- causal-lm
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inference: false
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---
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# CyberAgentLM2-7B (CALM2-7B)
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## Model Description
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CyberAgentLM2 is a decoder-only language model pre-trained on the 1.3T tokens of publicly available Japanese and English datasets.
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Variant: [CyberAgentLM2-Chat](https://huggingface.co/cyberagent/calm2-7b-chat)
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## Requirements
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- transformers >= 4.34.1
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- accelerate
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## Usage
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```python
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import transformers
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
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assert transformers.__version__ >= "4.34.1"
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model = AutoModelForCausalLM.from_pretrained("cyberagent/calm2-7b", device_map="auto", torch_dtype="auto")
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tokenizer = AutoTokenizer.from_pretrained("cyberagent/calm2-7b")
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streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
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prompt = "AIによって私達の暮らしは、"
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token_ids = tokenizer.encode(prompt, return_tensors="pt")
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output_ids = model.generate(
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input_ids=token_ids.to(model.device),
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max_new_tokens=100,
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do_sample=True,
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temperature=0.9,
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streamer=streamer,
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)
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```
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## Model Details
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* **Model size**: 7B
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* **Trained tokens**: 1.3T tokens
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* **Context length**: 4096
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* **Model type**: Transformer-based Language Model
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* **Language(s)**: Japanese, English
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* **Developed by**: [CyberAgent, Inc.](https://www.cyberagent.co.jp/)
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* **License**: Apache-2.0
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## Author
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[Ryosuke Ishigami](https://huggingface.co/rishigami)
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## Citations
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```tex
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@article{touvron2023llama,
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title={LLaMA: Open and Efficient Foundation Language Models},
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author={Touvron, Hugo and Lavril, Thibaut and Izacard, Gautier and Martinet, Xavier and Lachaux, Marie-Anne and Lacroix, Timoth{\'e}e and Rozi{\`e}re, Baptiste and Goyal, Naman and Hambro, Eric and Azhar, Faisal and Rodriguez, Aurelien and Joulin, Armand and Grave, Edouard and Lample, Guillaume},
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journal={arXiv preprint arXiv:2302.13971},
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year={2023}
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}
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``` |