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
File size: 443 Bytes
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"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
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],
"image_processor_type": "Qwen2VLImageProcessor",
"image_std": [
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],
"merge_size": 2,
"patch_size": 16,
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
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"temporal_patch_size": 2
}
|