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Wenwen Qu dccdfc7e4e support mixtral-7x8b		2024-01-16 19:23:11 +08:00
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internlm_model	feat(model): support llama model with checkpoint loading (#532 )	2023-12-11 16:25:24 +08:00
README-zh-Hans.md	[Develop] Pull Main Branch (#121 )	2023-07-21 20:44:33 +08:00
README.md	[Develop] Pull Main Branch (#121 )	2023-07-21 20:44:33 +08:00
convert2hf.py	fix(tools): set bos, eos, pad in convert2hf to fix improper generation (#471 )	2023-11-07 23:10:06 +08:00
interface.py	feat(tools): support origin internlm architecture in web_demo (#478 )	2023-11-09 20:01:55 +08:00
intern_moss_example.py	initial commit	2023-07-06 12:55:23 +08:00
internlm_sft_on_moss.py	initial commit	2023-07-06 12:55:23 +08:00
mixtral2llamamoe.py	support mixtral-7x8b	2024-01-16 19:23:11 +08:00

README.md

InternLM Transformers

English | 简体中文

This folder contains the InternLM model in transformers format.

Weight Conversion

convert2hf.py can convert saved training weights into the transformers format with a single command. Execute the command in the root directory of repository:

python tools/transformers/convert2hf.py --src_folder origin_ckpt/ --tgt_folder hf_ckpt/ --tokenizer ./tools/V7_sft.model

Then, you can load it using the from_pretrained interface:

>>> from transformers import AutoTokenizer, AutoModel
>>> model = AutoModel.from_pretrained("hf_ckpt/", trust_remote_code=True).cuda()

intern_moss_example.py demonstrates an example of how to use LoRA for fine-tuning on the fnlp/moss-moon-002-sft dataset.