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
Upload LoRA adapter
Browse files- adapter_config.json +2 -2
- adapters.safetensors +1 -1
adapter_config.json
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@@ -7,7 +7,7 @@
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"fine_tune_type": "lora",
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"grad_accumulation_steps": 2,
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"grad_checkpoint": true,
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"iters":
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"learning_rate": 3e-05,
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"lora_parameters": {
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"rank": 16,
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"warmup": 50,
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"arguments": [
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3e-05,
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-
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1e-06
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]
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},
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"fine_tune_type": "lora",
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"grad_accumulation_steps": 2,
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"grad_checkpoint": true,
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"iters": 1700,
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"learning_rate": 3e-05,
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"lora_parameters": {
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"rank": 16,
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"warmup": 50,
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"arguments": [
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3e-05,
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1700,
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1e-06
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]
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},
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adapters.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 42229570
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version https://git-lfs.github.com/spec/v1
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oid sha256:c3e4251bf4af1bf7a53b81fd7f3f3d8f4f1548eba32d49b3afd085bc0f37d3c4
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size 42229570
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