Instructions to use Jignesh2619/gemma4-fatigue-detection-lora-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jignesh2619/gemma4-fatigue-detection-lora-v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Jignesh2619/gemma4-fatigue-detection-lora-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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Download README.md from Jignesh2619/gemma4-fatigue-detection-lora-v2: direct link, hf CLI and curl.
- Browser
- Download file 539 Bytes
-
https://huggingface.co/Jignesh2619/gemma4-fatigue-detection-lora-v2/resolve/main/README.md
- Command line
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hf download hf://Jignesh2619/gemma4-fatigue-detection-lora-v2/README.md
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curl -L -o README.md https://huggingface.co/Jignesh2619/gemma4-fatigue-detection-lora-v2/resolve/main/README.md
539 Bytes
metadata
base_model: unsloth/gemma-4-E2B-it
tags:
- text-generation-inference
- transformers
- unsloth
- gemma4
- trl
license: apache-2.0
language:
- en
Uploaded model
- Developed by: Jignesh2619
- License: apache-2.0
- Finetuned from model : unsloth/gemma-4-E2B-it
This gemma4 model was trained 2x faster with Unsloth
