metadata
license: apache-2.0
language:
- ja
- en
tags:
- japanese
- causal-lm
inference: false
This is a conversion of cyberagent/calm2-7b to safetensors so you don't have to worry about getting hacked by downloading dirty pickled files.
Original model card:
CyberAgentLM2-7B (CALM2-7B)
Model Description
CyberAgentLM2 is a decoder-only language model pre-trained on the 1.3T tokens of publicly available Japanese and English datasets.
Variant: CyberAgentLM2-Chat
Requirements
- transformers >= 4.34.1
- accelerate
Usage
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,
)
Model Details
- Model size: 7B
- Trained tokens: 1.3T tokens
- Context length: 4096
- Model type: Transformer-based Language Model
- Language(s): Japanese, English
- Developed by: CyberAgent, Inc.
- License: Apache-2.0
Author
Citations
@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}
}