Instructions to use l3utterfly/mistral-7b-v0.1-layla-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use l3utterfly/mistral-7b-v0.1-layla-v4 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="l3utterfly/mistral-7b-v0.1-layla-v4")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("l3utterfly/mistral-7b-v0.1-layla-v4")
model = AutoModelForCausalLM.from_pretrained("l3utterfly/mistral-7b-v0.1-layla-v4")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use l3utterfly/mistral-7b-v0.1-layla-v4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "l3utterfly/mistral-7b-v0.1-layla-v4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "l3utterfly/mistral-7b-v0.1-layla-v4",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/l3utterfly/mistral-7b-v0.1-layla-v4

SGLang

How to use l3utterfly/mistral-7b-v0.1-layla-v4 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 "l3utterfly/mistral-7b-v0.1-layla-v4" \
    --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": "l3utterfly/mistral-7b-v0.1-layla-v4",
		"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 "l3utterfly/mistral-7b-v0.1-layla-v4" \
        --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": "l3utterfly/mistral-7b-v0.1-layla-v4",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use l3utterfly/mistral-7b-v0.1-layla-v4 with Docker Model Runner:
```
docker model run hf.co/l3utterfly/mistral-7b-v0.1-layla-v4
```

mistral-7b-v0.1-layla-v4

Commit History

Adding Evaluation Results (#1)

a6f7706
verified

l3utterfly

leaderboard-pr-bot commited on Mar 11, 2024

Update README.md

14aaf56
verified

l3utterfly commited on Mar 11, 2024

Update README.md

f2f29e3
verified

l3utterfly commited on Mar 11, 2024

Create README.md

c98e049
verified

l3utterfly commited on Feb 28, 2024

cradle

50ea7f0

l3utterfly commited on Feb 28, 2024

initial commit

ecabf89
verified

l3utterfly commited on Feb 28, 2024

Commit History

Adding Evaluation Results (#1) a6f7706 verified

Update README.md 14aaf56 verified

Update README.md f2f29e3 verified

Create README.md c98e049 verified

cradle 50ea7f0

initial commit ecabf89 verified

Adding Evaluation Results (#1)

a6f7706
verified

Update README.md

14aaf56
verified

Update README.md

f2f29e3
verified

Create README.md

c98e049
verified

cradle

50ea7f0

initial commit

ecabf89
verified