Instructions to use roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF
- SGLang
How to use roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF 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 "roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF" \ --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": "roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF", "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 "roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF" \ --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": "roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF with Docker Model Runner:
docker model run hf.co/roleplaiapp/Midnight-Miqu-70B-v1.5-i1-Q6_K-GGUF
- Xet hash:
- a5da7942532000ea3c5dc1df5d1a37c565fdae7fb6bda8680275c113f3cef022
- Size of remote file:
- 29 GB
- SHA256:
- df372592c712f2b16e0e3238a5b5a3ee0658bed0631fc945cb0e85434d2257e3
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