Text Generation
PEFT
Safetensors
English
qwen3_5
healthcare
medical
clinical-reasoning
chain-of-thought
grounded-generation
hallucination-mitigation
safety
adaptive-data
autoscientist
lora
qwen
fine-tuned
conversational
Instructions to use hetanshwaghela/autoscientist-healthcare-reasoning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hetanshwaghela/autoscientist-healthcare-reasoning with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-0.8B") model = PeftModel.from_pretrained(base_model, "hetanshwaghela/autoscientist-healthcare-reasoning") - Notebooks
- Google Colab
- Kaggle
Add live demo link
Browse files
README.md
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- Adapted dataset id: `26048b57-f164-46d5-810b-12d498a76660` (20,000 rows)
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- Dataset: https://huggingface.co/datasets/hetanshwaghela/autoscientist-healthcare-reasoning
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- Kaggle model: https://www.kaggle.com/models/hetanshwaghela1/autoscientist-healthcare-reasoning
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## Credit
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**Built with Adaptive Data by Adaption.** Base: `Qwen/Qwen3.5-0.8B`. Foundation data:
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- Adapted dataset id: `26048b57-f164-46d5-810b-12d498a76660` (20,000 rows)
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- Dataset: https://huggingface.co/datasets/hetanshwaghela/autoscientist-healthcare-reasoning
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- Kaggle model: https://www.kaggle.com/models/hetanshwaghela1/autoscientist-healthcare-reasoning
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- 🧪 Live demo (HF Space): https://huggingface.co/spaces/hetanshwaghela/autoscientist-healthcare-demo
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## Credit
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**Built with Adaptive Data by Adaption.** Base: `Qwen/Qwen3.5-0.8B`. Foundation data:
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