Text Generation
Transformers
Safetensors
English
apollo
video
video-understanding
vision
multimodal
conversational
custom_code
instruction-tuning
Instructions to use GoodiesHere/Apollo-LMMs-Apollo-3B-t32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GoodiesHere/Apollo-LMMs-Apollo-3B-t32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="GoodiesHere/Apollo-LMMs-Apollo-3B-t32", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("GoodiesHere/Apollo-LMMs-Apollo-3B-t32", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use GoodiesHere/Apollo-LMMs-Apollo-3B-t32 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GoodiesHere/Apollo-LMMs-Apollo-3B-t32" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GoodiesHere/Apollo-LMMs-Apollo-3B-t32", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/GoodiesHere/Apollo-LMMs-Apollo-3B-t32
- SGLang
How to use GoodiesHere/Apollo-LMMs-Apollo-3B-t32 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 "GoodiesHere/Apollo-LMMs-Apollo-3B-t32" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GoodiesHere/Apollo-LMMs-Apollo-3B-t32", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "GoodiesHere/Apollo-LMMs-Apollo-3B-t32" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GoodiesHere/Apollo-LMMs-Apollo-3B-t32", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use GoodiesHere/Apollo-LMMs-Apollo-3B-t32 with Docker Model Runner:
docker model run hf.co/GoodiesHere/Apollo-LMMs-Apollo-3B-t32
Download configuration.json from GoodiesHere/Apollo-LMMs-Apollo-3B-t32: direct link, hf CLI and curl.
- Browser
- Download file 73 Bytes
-
https://huggingface.co/GoodiesHere/Apollo-LMMs-Apollo-3B-t32/resolve/f01c2b454fd0752ae9c3ec4aebbc3ae00f050fff/configuration.json
- Command line
-
hf download hf://GoodiesHere/Apollo-LMMs-Apollo-3B-t32@f01c2b454fd0752ae9c3ec4aebbc3ae00f050fff/configuration.json
-
curl -L -o configuration.json https://huggingface.co/GoodiesHere/Apollo-LMMs-Apollo-3B-t32/resolve/f01c2b454fd0752ae9c3ec4aebbc3ae00f050fff/configuration.json
73 Bytes
| {"framework": "pytorch", "task": "text-generation", "allow_remote": true} |