Instructions to use Punter1504/topic_balanced_2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Punter1504/topic_balanced_2000 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Punter1504/topic_balanced_2000", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use Punter1504/topic_balanced_2000 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 Punter1504/topic_balanced_2000 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 Punter1504/topic_balanced_2000 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Punter1504/topic_balanced_2000 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Punter1504/topic_balanced_2000", max_seq_length=2048, )
- Xet hash:
- 321c9d387166d56fb5ff253d52f0bcdd70d34294969d28478bad3ec774622b0a
- Size of remote file:
- 778 MB
- SHA256:
- 6b2719e327acfe1af23f2142a3cf5f447b110994d5135270df9add4fbcc6a7a0
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