Instructions to use Novaspree/factify-3B-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Novaspree/factify-3B-adapter with Transformers:

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

pipe = pipeline("text-generation", model="Novaspree/factify-3B-adapter")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Novaspree/factify-3B-adapter", dtype="auto")

PEFT
How to use Novaspree/factify-3B-adapter with PEFT:
```
Task type is invalid.
```
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Novaspree/factify-3B-adapter with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Novaspree/factify-3B-adapter"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Novaspree/factify-3B-adapter",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Novaspree/factify-3B-adapter

SGLang

How to use Novaspree/factify-3B-adapter 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 "Novaspree/factify-3B-adapter" \
    --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": "Novaspree/factify-3B-adapter",
		"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 "Novaspree/factify-3B-adapter" \
        --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": "Novaspree/factify-3B-adapter",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Novaspree/factify-3B-adapter with Docker Model Runner:
```
docker model run hf.co/Novaspree/factify-3B-adapter
```

Improve model card and add metadata

by nielsr HF Staff - opened 9 days ago

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+33

-184

nielsr

9 days ago

This PR improves the model card by:

Adding relevant metadata including the license, base model, library name, and pipeline tag.
Providing a description of the MAAT (Multi-phase Adapter-Aware Targeted Unlearning) framework and the 5WBENCH benchmark.
Linking to the paper and official GitHub repository.
Specifying the target dataset (TOFU) based on the repository context.

Improve model card and add metadata01e390c3

Novaspree changed pull request status to merged 8 days ago

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