Instructions to use TianHuiLab/Falcon-Single-Instruction-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TianHuiLab/Falcon-Single-Instruction-Base with Transformers:

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

pipe = pipeline("image-text-to-text", model="TianHuiLab/Falcon-Single-Instruction-Base")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("TianHuiLab/Falcon-Single-Instruction-Base", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use TianHuiLab/Falcon-Single-Instruction-Base with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/TianHuiLab/Falcon-Single-Instruction-Base

SGLang

How to use TianHuiLab/Falcon-Single-Instruction-Base 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 "TianHuiLab/Falcon-Single-Instruction-Base" \
    --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": "TianHuiLab/Falcon-Single-Instruction-Base",
		"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 "TianHuiLab/Falcon-Single-Instruction-Base" \
        --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": "TianHuiLab/Falcon-Single-Instruction-Base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TianHuiLab/Falcon-Single-Instruction-Base with Docker Model Runner:
```
docker model run hf.co/TianHuiLab/Falcon-Single-Instruction-Base
```

You need to agree to share your contact information to access this model

The information you provide will be collected, stored, processed and shared in accordance with the Meta Privacy Policy.

Falcon COMMUNITY LICENSE AGREEMENT

Please specify the organization and the user's name. Submissions with incomplete information may be rejected.

README.md exists but content is empty.

Downloads last month: -; Downloads are not tracked for this model. How to track

Inference Providers NEW

Image-Text-to-Text

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support