Instructions to use josephmayo/ZAYA1-8B-Coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use josephmayo/ZAYA1-8B-Coder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="josephmayo/ZAYA1-8B-Coder") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("josephmayo/ZAYA1-8B-Coder", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use josephmayo/ZAYA1-8B-Coder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "josephmayo/ZAYA1-8B-Coder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "josephmayo/ZAYA1-8B-Coder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/josephmayo/ZAYA1-8B-Coder
- SGLang
How to use josephmayo/ZAYA1-8B-Coder 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 "josephmayo/ZAYA1-8B-Coder" \ --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": "josephmayo/ZAYA1-8B-Coder", "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 "josephmayo/ZAYA1-8B-Coder" \ --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": "josephmayo/ZAYA1-8B-Coder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use josephmayo/ZAYA1-8B-Coder with Docker Model Runner:
docker model run hf.co/josephmayo/ZAYA1-8B-Coder
| { | |
| "base_model": "Zyphra/ZAYA1-8B", | |
| "adapter_repo": "josephmayo/ZAYA1-8B-Coding-LoRA", | |
| "num_prompts": 50, | |
| "base_avg": 2.36, | |
| "lora_avg": 4.76, | |
| "improved_count": 39, | |
| "improvement_pct_full_scale": 24.0, | |
| "merge_threshold_pct": 20.0, | |
| "should_merge": true, | |
| "scoring": { | |
| "def": 2, | |
| "class": 1, | |
| "return": 1, | |
| "import_or_from": 1, | |
| "code_block": 1, | |
| "length_gt_100_chars": 1, | |
| "ast_parse_valid": 3, | |
| "max": 10 | |
| } | |
| } |