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InternLM
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Merge pull request #7 from 00INDEX/main 

Update: Readme
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Xingcheng Zhang 2023-07-06 16:50:25 +08:00 committed by GitHub
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README-zh-Hans.md
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@ -76,7 +76,7 @@ InternLM ，即书生·浦语大模型，包含面向实用场景的70亿参数
```python
>>> from transformers import AutoTokenizer, AutoModelForCausalLM
>>> tokenizer = AutoTokenizer.from_pretrained("internlm/internlm-chat-7b", trust_remote_code=True)
>>> model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b", trust_remote_code=True, device='cuda')
>>> model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b", trust_remote_code=True).cuda()
>>> model = model.eval()
>>> response, history = model.chat(tokenizer, "你好", history=[])
>>> print(response)
@ -137,7 +137,7 @@ python convert2hf.py --src_folder origin_ckpt/ --tgt_folder hf_ckpt/ --tokenizer
转换之后可以通过以下的代码加载为 transformers
```python
>>> from transformers import AutoTokenizer, AutoModel
>>> model = AutoModel.from_pretrained("hf_ckpt/", trust_remote_code=True, device='cuda')
>>> model = AutoModel.from_pretrained("hf_ckpt/", trust_remote_code=True).cuda()
```

2
README.md
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@ -144,7 +144,7 @@ python convert2hf.py --src_folder origin_ckpt/ --tgt_folder hf_ckpt/ --tokenizer
After conversion, it can be loaded as transformers by the following code
```python
>>> from transformers import AutoTokenizer, AutoModel
>>> model = AutoModel.from_pretrained("hf_ckpt/", trust_remote_code=True, device='cuda')
>>> model = AutoModel.from_pretrained("hf_ckpt/", trust_remote_code=True).cuda()
```