Instructions to use eachadea/legacy-vicuna-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eachadea/legacy-vicuna-13b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="eachadea/legacy-vicuna-13b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("eachadea/legacy-vicuna-13b") model = AutoModelForCausalLM.from_pretrained("eachadea/legacy-vicuna-13b") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use eachadea/legacy-vicuna-13b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "eachadea/legacy-vicuna-13b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "eachadea/legacy-vicuna-13b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/eachadea/legacy-vicuna-13b
- SGLang
How to use eachadea/legacy-vicuna-13b with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "eachadea/legacy-vicuna-13b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "eachadea/legacy-vicuna-13b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "eachadea/legacy-vicuna-13b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "eachadea/legacy-vicuna-13b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use eachadea/legacy-vicuna-13b with Docker Model Runner:
docker model run hf.co/eachadea/legacy-vicuna-13b
Adding `safetensors` variant of this model
#10 opened over 1 year ago
by
SFconvertbot
Adding Evaluation Results
#9 opened over 2 years ago
by
leaderboard-pr-bot
Adding Evaluation Results
#8 opened over 2 years ago
by
leaderboard-pr-bot
Model taking too much time
#7 opened about 3 years ago
by
kanwalkhalid
how to get 30B vicuna
3
#6 opened about 3 years ago
by
baby1
what's the origin train data
2
#5 opened about 3 years ago
by
baby1
Update README.md
1
#4 opened over 3 years ago
by
thawani
OSError: Unable to load weights from pytorch checkpoint file for './vicuna-13b/pytorch_model-00002-of-00003.bin' at
๐ 1
#3 opened over 3 years ago
by
hswu
Tokenizer class LlamaTokenizer does not exist
๐ 8
8
#2 opened over 3 years ago
by
xerxes01