Instructions to use Joaoffg/SHARE-4B-Base-2604 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Joaoffg/SHARE-4B-Base-2604 with Transformers:

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

pipe = pipeline("text-generation", model="Joaoffg/SHARE-4B-Base-2604")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Joaoffg/SHARE-4B-Base-2604")
model = AutoModelForCausalLM.from_pretrained("Joaoffg/SHARE-4B-Base-2604")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Joaoffg/SHARE-4B-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-4B-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-4B-Base-2604",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Joaoffg/SHARE-4B-Base-2604

SGLang

How to use Joaoffg/SHARE-4B-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-4B-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-4B-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-4B-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-4B-Base-2604",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Joaoffg/SHARE-4B-Base-2604 with Docker Model Runner:
```
docker model run hf.co/Joaoffg/SHARE-4B-Base-2604
```

Add pipeline tag, library name, and paper link

by nielsr HF Staff - opened Apr 15

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-4

nielsr

Apr 15

This PR improves the model card by adding relevant metadata and linking the research paper:

pipeline_tag: text-generation: Ensures the model is correctly categorized on the Hub.
library_name: transformers: Identifies the compatible library based on the Phi3ForCausalLM architecture.
Paper link: Connects the model to its research paper SHARE: Social-Humanities AI for Research and Education.

Add pipeline tag, library name, and paper link211177b2

Joaoffg changed pull request status to merged Apr 15

Joaoffg deleted the refs/pr/1 ref Apr 15

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