Instructions to use GeneroGral/Mistral-Nemo-12B_BBQ_Stereo_MERGED6_dropout_batch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GeneroGral/Mistral-Nemo-12B_BBQ_Stereo_MERGED6_dropout_batch with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GeneroGral/Mistral-Nemo-12B_BBQ_Stereo_MERGED6_dropout_batch", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use GeneroGral/Mistral-Nemo-12B_BBQ_Stereo_MERGED6_dropout_batch 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 GeneroGral/Mistral-Nemo-12B_BBQ_Stereo_MERGED6_dropout_batch 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 GeneroGral/Mistral-Nemo-12B_BBQ_Stereo_MERGED6_dropout_batch to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for GeneroGral/Mistral-Nemo-12B_BBQ_Stereo_MERGED6_dropout_batch to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="GeneroGral/Mistral-Nemo-12B_BBQ_Stereo_MERGED6_dropout_batch", max_seq_length=2048, )
- Xet hash:
- cdb01f62778a8fd2c8661747919180a217fcb2acf0c1fccc42623721965b144c
- Size of remote file:
- 4.87 GB
- SHA256:
- 5bbc3d32534f781a8558b9f848c29d786dab60b6aaab37b7c68e80e487b1f533
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