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
- 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
Upload generation_config.json (max2-nano weights)
Browse files- generation_config.json +22 -0
generation_config.json
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{
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"architectures": [
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"Max2ForCausalLM"
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],
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"model_type": "max2",
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"model_name": "max2-nano",
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"hidden_size": 768,
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"intermediate_size": 2048,
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"num_hidden_layers": 12,
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"num_attention_heads": 12,
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"num_key_value_heads": 3,
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"vocab_size": 32000,
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"max_position_embeddings": 4096,
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"rope_theta": 10000.0,
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"use_moe": true,
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"num_experts": 4,
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"num_experts_per_tok": 1,
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"expert_hidden_size": 512,
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"rms_norm_eps": 1e-06,
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"torch_dtype": "float16",
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"transformers_version": "4.40.0"
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}
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