mirror of https://github.com/InternLM/InternLM
![]() * fix/fix_submodule_err (#61) * fix/fix_submodule_err --------- Co-authored-by: ChenQiaoling00 <qiaoling_chen@u.nus.edu> * fix issue templates (#65) * fix(tokenizer): refactor tokenizer and update usage in readme (#51) * update tokenizer example * fix(readme, requirements): fix typo at Chinese readme and select a lower version of transformers (#73) * fix a typo in readme * in order to find InternLMTokenizer, select a lower version of Transformers --------- Co-authored-by: gouhchangjiang <gouhchangjiang@gmail.com> * [Doc] Add wechat and discord link in readme (#78) * Doc:add wechat and discord link * Doc:update wechat and discord link * Doc:update wechat and discord link * Doc:update wechat and discord link * Doc:update wechat and discord link * Doc:update wechat and discord link * Doc:update wechat and discord link * Doc:update wechat and discord link * Doc:update wechat and discord link * Doc:update wechat and discord link * Doc:update wechat and discord link * [Docs]: add Japanese README (#43) * Add Japanese README * Update README-ja-JP.md replace message * Update README-ja-JP.md * add repetition_penalty in GenerationConfig in web_demo.py (#48) Co-authored-by: YWMditto <862779238@qq.com> * use fp16 in instruction (#80) * [Enchancement] add more options for issue template (#77) * [Enchancement] add more options for issue template * update qustion icon * fix link * Use tempfile for convert2hf.py (#23) Fix https://github.com/InternLM/InternLM/issues/50 * delete torch_dtype of README's example code (#100) * set the value of repetition_penalty to 1.0 to avoid random outputs (#99) * Update web_demo.py (#97) Remove meaningless log. * [Fix]Fix wrong string cutoff in the script for sft text tokenizing (#106) --------- Co-authored-by: ChenQiaoling00 <qiaoling_chen@u.nus.edu> Co-authored-by: Kai Chen <chenkaidev@gmail.com> Co-authored-by: Yang Gao <Gary1546308416AL@gmail.com> Co-authored-by: Changjiang GOU <gouchangjiang@gmail.com> Co-authored-by: gouhchangjiang <gouhchangjiang@gmail.com> Co-authored-by: vansin <msnode@163.com> Co-authored-by: Ikko Eltociear Ashimine <eltociear@gmail.com> Co-authored-by: YWMditto <46778265+YWMditto@users.noreply.github.com> Co-authored-by: YWMditto <862779238@qq.com> Co-authored-by: WRH <12756472+wangruohui@users.noreply.github.com> Co-authored-by: liukuikun <24622904+Harold-lkk@users.noreply.github.com> Co-authored-by: x54-729 <45304952+x54-729@users.noreply.github.com> Co-authored-by: Shuo Zhang <zhangshuolove@live.com> Co-authored-by: Miao Zheng <76149310+MeowZheng@users.noreply.github.com> |
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README-zh-Hans.md | ||
README.md | ||
configuration_internlm.py | ||
convert2hf.py | ||
intern_moss_example.py | ||
internlm_sft_on_moss.py | ||
modeling_internlm.py | ||
tokenization_internlm.py |
README.md
InternLM Transformers
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.