Instructions to use Joaoffg/SHARE-14B-Base-2604 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Joaoffg/SHARE-14B-Base-2604 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Joaoffg/SHARE-14B-Base-2604")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Joaoffg/SHARE-14B-Base-2604") model = AutoModelForCausalLM.from_pretrained("Joaoffg/SHARE-14B-Base-2604") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Joaoffg/SHARE-14B-Base-2604 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Joaoffg/SHARE-14B-Base-2604" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Joaoffg/SHARE-14B-Base-2604", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Joaoffg/SHARE-14B-Base-2604
- SGLang
How to use Joaoffg/SHARE-14B-Base-2604 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 "Joaoffg/SHARE-14B-Base-2604" \ --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": "Joaoffg/SHARE-14B-Base-2604", "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 "Joaoffg/SHARE-14B-Base-2604" \ --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": "Joaoffg/SHARE-14B-Base-2604", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Joaoffg/SHARE-14B-Base-2604 with Docker Model Runner:
docker model run hf.co/Joaoffg/SHARE-14B-Base-2604
Add library_name and pipeline_tag metadata
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the community science team at Hugging Face.
This PR improves the metadata and documentation of SHARE-14B:
- Added
library_name: transformersto enable the automated code snippet widget. - Added
pipeline_tag: text-generationfor better discoverability. - Updated
languagetags to include Dutch (nl). - Added links to the paper and the GitHub repository in the model description.
These changes help users find and use the model more effectively on the Hub!
Joaoffg changed pull request status to merged
Joaoffg deleted the
refs/pr/1 ref