Text Generation
Transformers
PyTorch
Spanish
gptj
Transformers
bertin-project/alpaca-spanish
PyTorch
alpaca
llm spanish
Instructions to use RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g") model = AutoModelForCausalLM.from_pretrained("RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g
- SGLang
How to use RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g 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 "RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g" \ --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": "RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g", "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 "RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g" \ --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": "RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g with Docker Model Runner:
docker model run hf.co/RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g
No funciona
#1
by leonardogt - opened
Hola, gran idea. Pero no funciona.
hola gracias por tu pregunta, dime m谩s detalles de c贸mo lo ejecutaste, recuerda que hay todo un tutorial en la descripci贸n del modelo, por ahora a m铆 me funciona perfectamente.