Text Generation
Transformers
Safetensors
English
minimind
minimax_m2
conversational
custom_code
fp8
max2
Mixture of Experts
mixture-of-experts
gqa
grouped-query-attention
edge-deployment
mobile
android
efficient
llama-cpp
causal-lm
Eval Results (legacy)
Instructions to use fariasultana/MiniMind with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fariasultana/MiniMind with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="fariasultana/MiniMind", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("fariasultana/MiniMind", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use fariasultana/MiniMind with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "fariasultana/MiniMind" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fariasultana/MiniMind", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/fariasultana/MiniMind
- SGLang
How to use fariasultana/MiniMind 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 "fariasultana/MiniMind" \ --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": "fariasultana/MiniMind", "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 "fariasultana/MiniMind" \ --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": "fariasultana/MiniMind", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use fariasultana/MiniMind with Docker Model Runner:
docker model run hf.co/fariasultana/MiniMind
feat: Add deployment module
Browse files- deployment/__init__.py +20 -0
deployment/__init__.py
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"""
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MiniMind Max2 Deployment Tools
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Docker, Kubernetes, and cloud deployment utilities.
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"""
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from .docker import (
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DockerConfig,
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DockerfileGenerator,
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DockerBuilder,
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OCIArtifactBuilder,
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create_docker_package,
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)
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__all__ = [
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"DockerConfig",
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"DockerfileGenerator",
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"DockerBuilder",
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"OCIArtifactBuilder",
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"create_docker_package",
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]
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