Instructions to use clibrain/Llama-2-ft-instruct-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use clibrain/Llama-2-ft-instruct-es with Transformers:

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

pipe = pipeline("text-generation", model="clibrain/Llama-2-ft-instruct-es")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("clibrain/Llama-2-ft-instruct-es")
model = AutoModelForCausalLM.from_pretrained("clibrain/Llama-2-ft-instruct-es")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use clibrain/Llama-2-ft-instruct-es with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "clibrain/Llama-2-ft-instruct-es"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "clibrain/Llama-2-ft-instruct-es",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/clibrain/Llama-2-ft-instruct-es

SGLang

How to use clibrain/Llama-2-ft-instruct-es 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 "clibrain/Llama-2-ft-instruct-es" \
    --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": "clibrain/Llama-2-ft-instruct-es",
		"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 "clibrain/Llama-2-ft-instruct-es" \
        --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": "clibrain/Llama-2-ft-instruct-es",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use clibrain/Llama-2-ft-instruct-es with Docker Model Runner:
```
docker model run hf.co/clibrain/Llama-2-ft-instruct-es
```

No puedo usar el modelo en google colab

by ClaudiaQueipo - opened Nov 10, 2023

Discussion

ClaudiaQueipo

Nov 10, 2023

Hola. Me alegra el excelente trabajo que ha hecho el equipo de clibrain. Tengo una duda hay alguna forma de que se pueda usar este modelo en Google Colab? es que trato pero se me cierra por los requisitos del modelo.

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