85 lines
2.4 KiB
Markdown
85 lines
2.4 KiB
Markdown
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---
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license: Apache License 2.0
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tasks:
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- text-generation
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language:
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- en
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library_name: transformers
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inference: false
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widgets:
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- task: text-generation
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version: 1
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inputs:
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- type: text
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name: text
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title: 输入文字
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validator:
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max_words: 128
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examples:
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- name: 1
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title: 示例1
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inputs:
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- name: text
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data: 你好
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inferencespec:
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cpu: 4
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memory: 24000
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gpu: 1
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gpu_memory: 16000
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---
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**NOTE: This model has delta files applied and can be used directly.**
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# Vicuna Model Card
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## Model details
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```
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pip install fschat
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```
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```python
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from modelscope.utils.constant import Tasks
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from modelscope.pipelines import pipeline
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pipe = pipeline(task=Tasks.text_generation, model='AI-ModelScope/Vicuna-7B', model_revision='v1.0.1', device='cuda')
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inputs = '你好'
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result = pipe(inputs)
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print(result)
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```
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**Model type:**
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Vicuna is an open-source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.
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It is an auto-regressive language model, based on the transformer architecture.
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**Model date:**
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Vicuna was trained between March 2023 and April 2023.
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**Organizations developing the model:**
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The Vicuna team with members from UC Berkeley, CMU, Stanford, and UC San Diego.
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**Paper or resources for more information:**
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https://vicuna.lmsys.org/
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**License:**
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Apache License 2.0
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**Where to send questions or comments about the model:**
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https://github.com/lm-sys/FastChat/issues
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## Intended use
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**Primary intended uses:**
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The primary use of Vicuna is research on large language models and chatbots.
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**Primary intended users:**
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The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.
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## Training dataset
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70K conversations collected from ShareGPT.com.
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## Evaluation dataset
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A preliminary evaluation of the model quality is conducted by creating a set of 80 diverse questions and utilizing GPT-4 to judge the model outputs. See https://vicuna.lmsys.org/ for more details.
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## Major updates of weights v1.1
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- Refactor the tokenization and separator. In Vicuna v1.1, the separator has been changed from `"###"` to the EOS token `"</s>"`. This change makes it easier to determine the generation stop criteria and enables better compatibility with other libraries.
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- Fix the supervised fine-tuning loss computation for better model quality.
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