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fix huggingface link (#219)

pull/57/head^2 v0.1.0
loveSnowBest 2023-08-22 22:20:01 +08:00 committed by GitHub
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4
README-ja-JP.md
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@ -84,8 +84,8 @@ Transformers を使用して InternLM 7B チャットモデルをロードする
```python
>>> from transformers import AutoTokenizer, AutoModelForCausalLM
>>> tokenizer = AutoTokenizer.from_pretrained("internlm/internlm-chat-7b-v1.1", trust_remote_code=True)
>>> model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b-v1.1", trust_remote_code=True).cuda()
>>> tokenizer = AutoTokenizer.from_pretrained("internlm/internlm-chat-7b-v1_1", trust_remote_code=True)
>>> model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b-v1_1", trust_remote_code=True).cuda()
>>> model = model.eval()
>>> response, history = model.chat(tokenizer, "こんにちは", history=[])
>>> print(response)

4
README-zh-Hans.md
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@ -90,8 +90,8 @@ 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-v1.1", trust_remote_code=True)
>>> model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b-v1.1", trust_remote_code=True).cuda()
>>> tokenizer = AutoTokenizer.from_pretrained("internlm/internlm-chat-7b-v1_1", trust_remote_code=True)
>>> model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b-v1_1", trust_remote_code=True).cuda()
>>> model = model.eval()
>>> response, history = model.chat(tokenizer, "你好", history=[])
>>> print(response)

4
README.md
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@ -90,8 +90,8 @@ To load the InternLM 7B Chat model using Transformers, use the following code:
```python
>>> from transformers import AutoTokenizer, AutoModelForCausalLM
>>> tokenizer = AutoTokenizer.from_pretrained("internlm/internlm-chat-7b-v1.1", trust_remote_code=True)
>>> model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b-v1.1", trust_remote_code=True).cuda()
>>> tokenizer = AutoTokenizer.from_pretrained("internlm/internlm-chat-7b-v1_1", trust_remote_code=True)
>>> model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b-v1_1", trust_remote_code=True).cuda()
>>> model = model.eval()
>>> response, history = model.chat(tokenizer, "hello", history=[])
>>> print(response)