Text Generation
Transformers
Safetensors
English
Chinese
minicpm
minicpm5
llama
long-context
tool-calling
on-device
edge-ai
Instructions to use openbmb/MiniCPM5-1B-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM5-1B-MLX with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="openbmb/MiniCPM5-1B-MLX")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM5-1B-MLX", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use openbmb/MiniCPM5-1B-MLX with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "openbmb/MiniCPM5-1B-MLX" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "openbmb/MiniCPM5-1B-MLX", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/openbmb/MiniCPM5-1B-MLX
- SGLang
How to use openbmb/MiniCPM5-1B-MLX 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 "openbmb/MiniCPM5-1B-MLX" \ --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": "openbmb/MiniCPM5-1B-MLX", "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 "openbmb/MiniCPM5-1B-MLX" \ --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": "openbmb/MiniCPM5-1B-MLX", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use openbmb/MiniCPM5-1B-MLX with Docker Model Runner:
docker model run hf.co/openbmb/MiniCPM5-1B-MLX
File size: 926 Bytes
92b4f50 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | {
"_name_or_path": "MiniCPM5-1B-MLX",
"architectures": [
"LlamaForCausalLM"
],
"bos_token_id": 0,
"eos_token_id": [
1,
130073
],
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 1536,
"initializer_range": 0.02,
"intermediate_size": 4608,
"max_position_embeddings": 131072,
"model_type": "llama",
"num_attention_heads": 16,
"num_hidden_layers": 24,
"num_key_value_heads": 2,
"pad_token_id": 1,
"quantization": {
"group_size": 64,
"bits": 4,
"mode": "affine"
},
"quantization_config": {
"group_size": 64,
"bits": 4,
"mode": "affine"
},
"rms_norm_eps": 1e-06,
"rope_scaling": null,
"rope_theta": 5000000,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "5.6.2",
"use_cache": true,
"vocab_size": 130560
} |