Text Generation
PEFT
Safetensors
English
medical
pathology
cancer
oncology
tcga
survival-analysis
clinical-nlp
instruction-tuning
lora
qlora
qwen2.5
unsloth
sft
trl
conversational
Eval Results (legacy)
Instructions to use drkareemkamal/PathQwen2.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use drkareemkamal/PathQwen2.5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-7B-Instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "drkareemkamal/PathQwen2.5") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
- Xet hash:
- 1bdf644f8d82c3e61c7e7cbd7bbbf974e8be7a27101ce9a038e9e2271b62689e
- Size of remote file:
- 5.82 kB
- SHA256:
- d086e9b0d7274b08f1008636bd58ef9921fdd2920d6dd14d50d29d9f2f7e40c9
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