Instructions to use derektan95/LISA-AVS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use derektan95/LISA-AVS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="derektan95/LISA-AVS")# Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("derektan95/LISA-AVS") model = AutoModelForCausalLM.from_pretrained("derektan95/LISA-AVS") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use derektan95/LISA-AVS with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "derektan95/LISA-AVS" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "derektan95/LISA-AVS", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/derektan95/LISA-AVS
- SGLang
How to use derektan95/LISA-AVS 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 "derektan95/LISA-AVS" \ --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": "derektan95/LISA-AVS", "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 "derektan95/LISA-AVS" \ --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": "derektan95/LISA-AVS", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use derektan95/LISA-AVS with Docker Model Runner:
docker model run hf.co/derektan95/LISA-AVS
Update README.md
Browse files
README.md
CHANGED
|
@@ -6,6 +6,8 @@ license: apache-2.0
|
|
| 6 |
# Model Card for LISA-RS
|
| 7 |
We fine-tune [LISA](https://github.com/dvlab-research/LISA) reasoning segmentation model with dataset from AVS training dataset from [AVS-Bench](https://huggingface.co/datasets/derektan95/avs-bench).
|
| 8 |
|
|
|
|
|
|
|
| 9 |
## Citation
|
| 10 |
```
|
| 11 |
@inproceedings{tan2025searchtta,
|
|
|
|
| 6 |
# Model Card for LISA-RS
|
| 7 |
We fine-tune [LISA](https://github.com/dvlab-research/LISA) reasoning segmentation model with dataset from AVS training dataset from [AVS-Bench](https://huggingface.co/datasets/derektan95/avs-bench).
|
| 8 |
|
| 9 |
+
For more information on usage, please refer to the [LISA-AVS Github repository here](https://github.com/marmotlab/LISA-AVS).
|
| 10 |
+
|
| 11 |
## Citation
|
| 12 |
```
|
| 13 |
@inproceedings{tan2025searchtta,
|