Text Classification
PEFT
Safetensors
English
biojev
biomedical
qwen3.5
qlora
natural-language-inference
biomedical-nlp
system-one
Instructions to use Gabriel382/BioJev-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Gabriel382/BioJev-9B with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("Qwen/Qwen3.5-9B-Base") model = PeftModel.from_pretrained(base_model, "Gabriel382/BioJev-9B") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Gabriel382/BioJev-9B: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/Gabriel382/BioJev-9B/resolve/main/tokenizer.json
- Command line
-
hf download hf://Gabriel382/BioJev-9B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Gabriel382/BioJev-9B/resolve/main/tokenizer.json
20 MB
- Xet hash:
- 27d2eee8f623e7d97acc63d53705a9359643550d64fbfba9f1bc7cdc95a8e547
- Size of remote file:
- 20 MB
- SHA256:
- f399b3cd12fa270d51457bb749fb30863521e8359b8a27059c71b6c2f7d6dd6c
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