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update readme related to internlm-chat-7v-v1.1 (#214)

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Kai Chen 2023-08-22 08:08:44 +08:00 committed by GitHub
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README-ja-JP.md
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@ -40,6 +40,10 @@ InternLM は、70 億のパラメータを持つベースモデルと、実用
さらに、大規模な依存関係を必要とせずにモデルの事前学習をサポートする軽量な学習フレームワークが提供されます。単一のコードベースで、数千の GPU を持つ大規模クラスタでの事前学習と、単一の GPU での微調整をサポートし、顕著な性能最適化を達成します。InternLM は、1024GPU でのトレーニングにおいて 90% 近いアクセラレーション効率を達成しています。
## 新闻
InternLM-7B-Chat v1.1 は、コード インタプリタと関数呼び出し機能を備えてリリースされました。 [Lagent](https://github.com/InternLM/lagent) で試すことができます。
## InternLM-7B
### パフォーマンス評価
@ -80,8 +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", trust_remote_code=True)
>>> model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b", 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)

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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", trust_remote_code=True)
>>> model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b", 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)

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README.md
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@ -47,8 +47,7 @@ Additionally, a lightweight training framework is offered to support model pre-t
## News
InternLM-7B-Chat v1.1 is released with code interpreter and function calling capability. You can try it with [Lagent](https://github.com/InternLM/lagent)
-
InternLM-7B-Chat v1.1 is released with code interpreter and function calling capability. You can try it with [Lagent](https://github.com/InternLM/lagent).
## InternLM-7B
@ -91,8 +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", trust_remote_code=True)
>>> model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b", 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)