Text Generation
Transformers
Safetensors
English
smartcoder_moe
Mixture of Experts
starcoder2
mixture-of-experts
code
smartcoder
conversational
custom_code
Instructions to use Johnblick187/SmartCoderMoE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Johnblick187/SmartCoderMoE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Johnblick187/SmartCoderMoE", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Johnblick187/SmartCoderMoE", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Johnblick187/SmartCoderMoE with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Johnblick187/SmartCoderMoE" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Johnblick187/SmartCoderMoE", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Johnblick187/SmartCoderMoE
- SGLang
How to use Johnblick187/SmartCoderMoE 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 "Johnblick187/SmartCoderMoE" \ --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": "Johnblick187/SmartCoderMoE", "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 "Johnblick187/SmartCoderMoE" \ --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": "Johnblick187/SmartCoderMoE", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Johnblick187/SmartCoderMoE with Docker Model Runner:
docker model run hf.co/Johnblick187/SmartCoderMoE
| { | |
| "architectures": ["SmartCoderMoEForCausalLM"], | |
| "model_type": "smartcoder_moe", | |
| "hidden_size": 2048, | |
| "num_hidden_layers": 40, | |
| "num_attention_heads": 16, | |
| "num_key_value_heads": 4, | |
| "intermediate_size": 8192, | |
| "vocab_size": 65536, | |
| "max_position_embeddings": 16384, | |
| "rope_theta": 999999.0, | |
| "sliding_window": null, | |
| "use_cache": true, | |
| "tie_word_embeddings": false, | |
| "norm_epsilon": 1e-5, | |
| "bos_token_id": 0, | |
| "eos_token_id": 0, | |
| "pad_token_id": 0, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "5.9.0", | |
| "n_experts": 32, | |
| "expert_dim": 512, | |
| "top_k": 2, | |
| "total_experts": 1280, | |
| "dense_intermediate": 8192, | |
| "auto_map": { | |
| "AutoConfig": "modeling_smartcoder_moe.SmartCoderMoEConfig", | |
| "AutoModelForCausalLM": "modeling_smartcoder_moe.SmartCoderMoEForCausalLM" | |
| } | |
| } |