How to use from
Unsloth Studio
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for omareng/on-device-LLM-gpt-oss-20b to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for omareng/on-device-LLM-gpt-oss-20b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for omareng/on-device-LLM-gpt-oss-20b to start chatting
Load model with FastModel
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="omareng/on-device-LLM-gpt-oss-20b",
    max_seq_length=2048,
)
Quick Links

Configuration Parsing Warning:In adapter_config.json: "peft.task_type" must be a string

GPT-OSS 20B Fine-tuned for Medical Radiology Diagnosis

LoRA fine-tuned version of unsloth/gpt-oss-20b for medical radiology diagnosis tasks.

Model Details

  • Base Model: unsloth/gpt-oss-20b
  • Fine-tuning Method: LoRA (Low-Rank Adaptation)
  • Training Framework: Unsloth
  • Task: Medical diagnosis from radiology reports
  • Training Dataset: Eurorad medical cases

Installation

pip install unsloth peft transformers accelerate bitsandbytes

Usage

from unsloth import FastLanguageModel
from peft import PeftModel

# Load base model
model, tokenizer = FastLanguageModel.from_pretrained(
    model_name="unsloth/gpt-oss-20b",
    dtype=None,
    max_seq_length=4096,
    load_in_4bit=True,
    full_finetuning=False,
)

# Load LoRA adapter
model = PeftModel.from_pretrained(
    model, 
    "omareng/on-device-LLM-gpt-oss-20b",
    is_trainable=False
)

# Enable inference mode
FastLanguageModel.for_inference(model)

Training Details

  • Framework: Unsloth
  • Dataset: Eurorad medical radiology cases
  • Optimization: 4-bit quantization
  • Sequence Length: 4096 tokens
  • Adapter Size: 2.27 GB

Citation

[Citation information will be added upon publication]

Limitations

  • Clinical Validation Required: This model has not been clinically validated and should not be used for actual patient diagnosis
  • Not for Clinical Use: Not intended for direct patient care without clinical validation
  • Research Purposes Only: Designed for research in medical AI and diagnostic systems
  • May reflect biases present in training data
  • Performance may vary across medical specialties
  • Like all LLMs, may generate plausible but incorrect information

Contact

Issues: Please report to this repository


Disclaimer: This model is for research purposes only and has not been approved for clinical use. Always consult qualified healthcare professionals for medical decisions.

Downloads last month
2
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for omareng/on-device-LLM-gpt-oss-20b

Adapter
(56)
this model