Instructions to use Marmara-NLP/CSE4078S25_Grp1_gemma3-1b-r16-tr-ner-lr5e-5-BASEMODEL 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-lr5e-5-BASEMODEL with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Marmara-NLP/CSE4078S25_Grp1_gemma3-1b-r16-tr-ner-lr5e-5-BASEMODEL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Marmara-NLP/CSE4078S25_Grp1_gemma3-1b-r16-tr-ner-lr5e-5-BASEMODEL 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-lr5e-5-BASEMODEL 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-lr5e-5-BASEMODEL 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-lr5e-5-BASEMODEL 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-lr5e-5-BASEMODEL", max_seq_length=2048, )
- Xet hash:
- 81d0f3487134430dfa79cfe1b1a89098ce474469e9ab56f203730679d99951d7
- Size of remote file:
- 52.2 MB
- SHA256:
- 1b4f1254c4f9c0df2ae6b25b9ef16b4b27bee9be4850975f704ec1057782881c
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