Instructions to use josephmayo/HRM-Text-1B-sft-code-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use josephmayo/HRM-Text-1B-sft-code-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("sapientinc/HRM-Text-1B") model = PeftModel.from_pretrained(base_model, "josephmayo/HRM-Text-1B-sft-code-LoRA") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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LoRA adapter for `sapientinc/HRM-Text-1B`.
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[`josephmayo/HRM-Text-1B-sft-code`](https://huggingface.co/josephmayo/HRM-Text-1B-sft-code)
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## Validation
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## Usage
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## Notes
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- This is an adapter, not a standalone merged model.
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LoRA adapter for `sapientinc/HRM-Text-1B`.
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`sapientinc/HRM-Text-1B` is a pretrained-only HRM text model. This adapter is the code post-training release built on top of it.
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The release uses supervised LoRA post-training for coding tasks. It is the adapter artifact; the merged model is:
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[`josephmayo/HRM-Text-1B-sft-code`](https://huggingface.co/josephmayo/HRM-Text-1B-sft-code)
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## Validation
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Local code validation:
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- Base model score: `5/100`
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- Adapter score: `24/100`
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- Absolute improvement: `+19/100`
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- Relative improvement: `4.8x` over base
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- HumanEval slice: `14/50`
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- MBPP slice: `10/50`
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The score above is the local validation result used for this release.
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## Usage
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## Notes
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- This is an adapter, not a standalone merged model.
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- This is the LoRA adapter. Use the merged model for standalone loading.
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