Instructions to use eachadea/legacy-vicuna-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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", device_map="auto")

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
```

Update README.md

by thawani - opened Apr 7, 2023

base: refs/heads/main

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thawani

Apr 7, 2023

No description provided.

Update README.md34ed0f25

kongbohu

Apr 12, 2023

python -m fastchat.serve.cli --model-name eachadea/vicuna-13b
usage: cli.py [-h] [--model-path MODEL_PATH] [--device {cpu,cuda,mps}] [--num-gpus NUM_GPUS] [--load-8bit] [--conv-template CONV_TEMPLATE] [--temperature TEMPERATURE]
[--max-new-tokens MAX_NEW_TOKENS] [--style {simple,rich}] [--debug]
cli.py: error: unrecognized arguments: --model-name eachadea/vicuna-13b

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