Instructions to use FreedomIntelligence/Apollo-72B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FreedomIntelligence/Apollo-72B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FreedomIntelligence/Apollo-72B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/Apollo-72B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use FreedomIntelligence/Apollo-72B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FreedomIntelligence/Apollo-72B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FreedomIntelligence/Apollo-72B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/FreedomIntelligence/Apollo-72B
- SGLang
How to use FreedomIntelligence/Apollo-72B 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 "FreedomIntelligence/Apollo-72B" \ --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": "FreedomIntelligence/Apollo-72B", "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 "FreedomIntelligence/Apollo-72B" \ --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": "FreedomIntelligence/Apollo-72B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use FreedomIntelligence/Apollo-72B with Docker Model Runner:
docker model run hf.co/FreedomIntelligence/Apollo-72B
Download model-00001-of-00031.safetensors from FreedomIntelligence/Apollo-72B: direct link, hf CLI and curl.
- Browser
- Download file 4.77 GB
-
https://huggingface.co/FreedomIntelligence/Apollo-72B/resolve/main/model-00001-of-00031.safetensors
- Command line
-
hf download hf://FreedomIntelligence/Apollo-72B/model-00001-of-00031.safetensors
-
curl -L -o model-00001-of-00031.safetensors https://huggingface.co/FreedomIntelligence/Apollo-72B/resolve/main/model-00001-of-00031.safetensors
4.77 GB
- Xet hash:
- 2d321c9772086ed9c7f9d21374b17272cb8cc5b66845cabb1cc79e089d6f1707
- Size of remote file:
- 4.77 GB
- SHA256:
- 8d35b81f50d371e421e0ec3b91d0d340a9db20e9bf18e7fce857741e0ffe734d
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