Instructions to use bharathmuppa/angular-coder-1.5b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use bharathmuppa/angular-coder-1.5b-lora with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download bharathmuppa/angular-coder-1.5b-lora --local-dir angular-coder-1.5b-lora
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from bharathmuppa/angular-coder-1.5b-lora: direct link, hf CLI and curl.
- Browser
- Download file 600 Bytes
-
https://huggingface.co/bharathmuppa/angular-coder-1.5b-lora/resolve/main/README.md
- Command line
-
hf download hf://bharathmuppa/angular-coder-1.5b-lora/README.md
-
curl -L -o README.md https://huggingface.co/bharathmuppa/angular-coder-1.5b-lora/resolve/main/README.md
600 Bytes
metadata
license: apache-2.0
base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
tags:
- angular
- lora
- mlx
library_name: mlx
angular-coder-1.5b-lora
The LoRA adapter behind bharathmuppa/angular-coder-1.5b. Apply it to
Qwen/Qwen2.5-Coder-1.5B-Instruct with mlx-lm:
python -m mlx_lm generate --model Qwen/Qwen2.5-Coder-1.5B-Instruct \
--adapter-path <this repo, downloaded> --prompt "What is new in Angular 20?"
Rank 16, scale 20, dropout 0.05, last 16 layers, keys: q/k/v/o projections and gate/up/down MLP projections. See the fused model card for data and training details.