Instructions to use Marmara-NLP/CSE4078S25_Grp1_gemma3-1b-r16-tr-ner-lr1e-4_2epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Marmara-NLP/CSE4078S25_Grp1_gemma3-1b-r16-tr-ner-lr1e-4_2epochs with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Marmara-NLP/CSE4078S25_Grp1_gemma3-1b-r16-tr-ner-lr1e-4_2epochs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Marmara-NLP/CSE4078S25_Grp1_gemma3-1b-r16-tr-ner-lr1e-4_2epochs with 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 Marmara-NLP/CSE4078S25_Grp1_gemma3-1b-r16-tr-ner-lr1e-4_2epochs 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 Marmara-NLP/CSE4078S25_Grp1_gemma3-1b-r16-tr-ner-lr1e-4_2epochs to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Marmara-NLP/CSE4078S25_Grp1_gemma3-1b-r16-tr-ner-lr1e-4_2epochs to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Marmara-NLP/CSE4078S25_Grp1_gemma3-1b-r16-tr-ner-lr1e-4_2epochs", max_seq_length=2048, )
- Xet hash:
- 8ad21c340c0478dfac7fb3b3ca5532c161d61593ec3d8aa78d29fa2f85d996e7
- Size of remote file:
- 52.2 MB
- SHA256:
- 5fad56941fcf592e2c783c6dc58527f0713d5b4feefd114b239cb5584df456ce
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