Instructions to use yolstacklok/cobol_coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use yolstacklok/cobol_coder with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="yolstacklok/cobol_coder", filename="unsloth.BF16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use yolstacklok/cobol_coder with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf yolstacklok/cobol_coder:BF16 # Run inference directly in the terminal: llama-cli -hf yolstacklok/cobol_coder:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf yolstacklok/cobol_coder:BF16 # Run inference directly in the terminal: llama-cli -hf yolstacklok/cobol_coder:BF16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf yolstacklok/cobol_coder:BF16 # Run inference directly in the terminal: ./llama-cli -hf yolstacklok/cobol_coder:BF16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf yolstacklok/cobol_coder:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf yolstacklok/cobol_coder:BF16
Use Docker
docker model run hf.co/yolstacklok/cobol_coder:BF16
- LM Studio
- Jan
- Ollama
How to use yolstacklok/cobol_coder with Ollama:
ollama run hf.co/yolstacklok/cobol_coder:BF16
- Unsloth Studio new
How to use yolstacklok/cobol_coder with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for yolstacklok/cobol_coder to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for yolstacklok/cobol_coder to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for yolstacklok/cobol_coder to start chatting
- Docker Model Runner
How to use yolstacklok/cobol_coder with Docker Model Runner:
docker model run hf.co/yolstacklok/cobol_coder:BF16
- Lemonade
How to use yolstacklok/cobol_coder with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull yolstacklok/cobol_coder:BF16
Run and chat with the model
lemonade run user.cobol_coder-BF16
List all available models
lemonade list
| { | |
| "_name_or_path": "unsloth/qwen2.5-coder-0.5b-bnb-4bit", | |
| "architectures": [ | |
| "Qwen2ForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 151643, | |
| "eos_token_id": 151643, | |
| "hidden_act": "silu", | |
| "hidden_size": 896, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4864, | |
| "max_position_embeddings": 32768, | |
| "max_window_layers": 24, | |
| "model_type": "qwen2", | |
| "num_attention_heads": 14, | |
| "num_hidden_layers": 24, | |
| "num_key_value_heads": 2, | |
| "pad_token_id": 151665, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": null, | |
| "rope_theta": 1000000.0, | |
| "sliding_window": null, | |
| "tie_word_embeddings": true, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.49.0", | |
| "unsloth_fixed": true, | |
| "unsloth_version": "2025.3.10", | |
| "use_cache": false, | |
| "use_mrope": false, | |
| "use_sliding_window": false, | |
| "vocab_size": 151936 | |
| } | |