CyberAgentLM2-7B (CALM2-7B)

模型说明

CyberAgentLM2 是一个仅解码器的语言模型，它在 1.3T tokens 的公开日语和英语数据集上进行了预训练。

环境要求

transformers >= 4.34.1
accelerate

使用方法

import transformers
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer

assert transformers.__version__ >= "4.34.1"

model = AutoModelForCausalLM.from_pretrained("cyberagent/calm2-7b", device_map="auto", torch_dtype="auto")
tokenizer = AutoTokenizer.from_pretrained("cyberagent/calm2-7b")
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)

prompt = "AIによって私達の暮らしは、"

token_ids = tokenizer.encode(prompt, return_tensors="pt")
output_ids = model.generate(
    input_ids=token_ids.to(model.device),
    max_new_tokens=100,
    do_sample=True,
    temperature=0.9,
    streamer=streamer,
)

模型详情

模型大小：7B
训练 tokens：1.3T tokens
上下文长度：4096
模型类型：基于 Transformer 的语言模型
支持语言：日语、英语
开发机构：CyberAgent, Inc.
许可证：Apache-2.0

作者

[Ryosuke Ishigami]

引用

@article{touvron2023llama,
  title={LLaMA: Open and Efficient Foundation Language Models},
  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},
  journal={arXiv preprint arXiv:2302.13971},
  year={2023}
}

CyberAgentLM2-7B (CALM2-7B)

模型说明

CyberAgentLM2 是一个仅解码器的语言模型，它在 1.3T tokens 的公开日语和英语数据集上进行了预训练。

变体：CyberAgentLM2-Chat

环境要求

transformers >= 4.34.1
accelerate

使用方法

import transformers
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer

assert transformers.__version__ >= "4.34.1"

model = AutoModelForCausalLM.from_pretrained("cyberagent/calm2-7b", device_map="auto", torch_dtype="auto")
tokenizer = AutoTokenizer.from_pretrained("cyberagent/calm2-7b")
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)

prompt = "AIによって私達の暮らしは、"

token_ids = tokenizer.encode(prompt, return_tensors="pt")
output_ids = model.generate(
    input_ids=token_ids.to(model.device),
    max_new_tokens=100,
    do_sample=True,
    temperature=0.9,
    streamer=streamer,
)

模型详情

模型大小：7B
训练 tokens：1.3T tokens
上下文长度：4096
模型类型：基于 Transformer 的语言模型
支持语言：日语、英语
开发机构：CyberAgent, Inc.
许可证：Apache-2.0

作者

[Ryosuke Ishigami]

引用

@article{touvron2023llama,
  title={LLaMA: Open and Efficient Foundation Language Models},
  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},
  journal={arXiv preprint arXiv:2302.13971},
  year={2023}
}