NOTE: This model has delta files applied and can be used directly.
pip install fschat
from modelscope.utils.constant import Tasks
from modelscope.pipelines import pipeline
pipe = pipeline(task=Tasks.text_generation, model='AI-ModelScope/Vicuna-7B', model_revision='v1.0.1', device='cuda')
inputs = '你好'
result = pipe(inputs)
print(result)
Model type:
Vicuna is an open-source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.
It is an auto-regressive language model, based on the transformer architecture.
Model date:
Vicuna was trained between March 2023 and April 2023.
Organizations developing the model:
The Vicuna team with members from UC Berkeley, CMU, Stanford, and UC San Diego.
Paper or resources for more information:
https://vicuna.lmsys.org/
License:
Apache License 2.0
Where to send questions or comments about the model:
https://github.com/lm-sys/FastChat/issues
Primary intended uses:
The primary use of Vicuna is research on large language models and chatbots.
Primary intended users:
The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.
70K conversations collected from ShareGPT.com.
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.
"###"
to the EOS token "</s>"
. This change makes it easier to determine the generation stop criteria and enables better compatibility with other libraries.