模型:
cyberagent/open-calm-7b
OpenCALM是由CyberAgent开发的一套仅解码器语言模型,预训练于日语数据集。
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("cyberagent/open-calm-7b", device_map="auto", torch_dtype=torch.float16)
tokenizer = AutoTokenizer.from_pretrained("cyberagent/open-calm-7b")
inputs = tokenizer("AIによって私達の暮らしは、", return_tensors="pt").to(model.device)
with torch.no_grad():
tokens = model.generate(
**inputs,
max_new_tokens=64,
do_sample=True,
temperature=0.7,
top_p=0.9,
repetition_penalty=1.05,
pad_token_id=tokenizer.pad_token_id,
)
output = tokenizer.decode(tokens[0], skip_special_tokens=True)
print(output)
| Model | Params | Layers | Dim | Heads | Dev ppl |
|---|---|---|---|---|---|
| 1232321 | 160M | 12 | 768 | 12 | 19.7 |
| 1233321 | 400M | 24 | 1024 | 16 | 13.8 |
| 1234321 | 830M | 24 | 1536 | 16 | 11.3 |
| 1235321 | 1.4B | 24 | 2048 | 16 | 10.3 |
| 1236321 | 2.7B | 32 | 2560 | 32 | 9.7 |
| 1237321 | 6.8B | 32 | 4096 | 32 | 8.2 |
@software{gpt-neox-library,
title = {{GPT-NeoX: Large Scale Autoregressive Language Modeling in PyTorch}},
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},
url = {https://www.github.com/eleutherai/gpt-neox},
doi = {10.5281/zenodo.5879544},
month = {8},
year = {2021},
version = {0.0.1},
}