Instructions to use llm-slice/pico-decoder-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use llm-slice/pico-decoder-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="llm-slice/pico-decoder-medium", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("llm-slice/pico-decoder-medium", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use llm-slice/pico-decoder-medium with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "llm-slice/pico-decoder-medium" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "llm-slice/pico-decoder-medium", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/llm-slice/pico-decoder-medium
- SGLang
How to use llm-slice/pico-decoder-medium 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 "llm-slice/pico-decoder-medium" \ --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": "llm-slice/pico-decoder-medium", "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 "llm-slice/pico-decoder-medium" \ --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": "llm-slice/pico-decoder-medium", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use llm-slice/pico-decoder-medium with Docker Model Runner:
docker model run hf.co/llm-slice/pico-decoder-medium
| { | |
| "activation_hidden_dim": 3072, | |
| "architectures": [ | |
| "PicoDecoderHF" | |
| ], | |
| "attention_n_heads": 12, | |
| "attention_n_kv_heads": 4, | |
| "auto_map": { | |
| "AutoConfig": "pico_decoder.PicoDecoderHFConfig", | |
| "AutoModelForCausalLM": "pico_decoder.PicoDecoderHF" | |
| }, | |
| "batch_size": 64, | |
| "d_model": 768, | |
| "max_seq_len": 128, | |
| "model_type": "pico_decoder", | |
| "n_layers": 12, | |
| "norm_eps": 1e-06, | |
| "position_emb_theta": 10000.0, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.51.0", | |
| "vocab_size": 50304 | |
| } | |