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:
- b3c29d9213350731338d47b82f0578715dc5ed817f4dec279ee3ec5ab197dc13
- Size of remote file:
- 4.91 GB
- SHA256:
- 343e0d0fc65733e92425995fef54ae30812cbb92a870af88186c2d35f81518d2
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