Instructions to use MayaPH/GodziLLa2-70B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MayaPH/GodziLLa2-70B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MayaPH/GodziLLa2-70B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("MayaPH/GodziLLa2-70B") model = AutoModelForCausalLM.from_pretrained("MayaPH/GodziLLa2-70B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use MayaPH/GodziLLa2-70B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MayaPH/GodziLLa2-70B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MayaPH/GodziLLa2-70B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/MayaPH/GodziLLa2-70B
- SGLang
How to use MayaPH/GodziLLa2-70B 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 "MayaPH/GodziLLa2-70B" \ --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": "MayaPH/GodziLLa2-70B", "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 "MayaPH/GodziLLa2-70B" \ --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": "MayaPH/GodziLLa2-70B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use MayaPH/GodziLLa2-70B with Docker Model Runner:
docker model run hf.co/MayaPH/GodziLLa2-70B
Download model-00021-of-00029.safetensors from MayaPH/GodziLLa2-70B: direct link, hf CLI and curl.
- Browser
- Download file 9.33 GB
-
https://huggingface.co/MayaPH/GodziLLa2-70B/resolve/78102fcdd6b801062c2ee8d6362830f469e627cf/model-00021-of-00029.safetensors
- Command line
-
hf download hf://MayaPH/GodziLLa2-70B@78102fcdd6b801062c2ee8d6362830f469e627cf/model-00021-of-00029.safetensors
-
curl -L -o model-00021-of-00029.safetensors https://huggingface.co/MayaPH/GodziLLa2-70B/resolve/78102fcdd6b801062c2ee8d6362830f469e627cf/model-00021-of-00029.safetensors
9.33 GB
- Xet hash:
- 55698f6b40bc5a147dbe36750b53fb22c353f4ecc12a960f72de638959ae26bc
- Size of remote file:
- 9.33 GB
- SHA256:
- 4fe1c6f180f07589cbee21a2b3f1ce7fa9ad832d292ffd4c4514e54841f95b03
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