Instructions to use Gunulhona/tbecmodel_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gunulhona/tbecmodel_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Gunulhona/tbecmodel_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Gunulhona/tbecmodel_v2") model = AutoModelForSequenceClassification.from_pretrained("Gunulhona/tbecmodel_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Gunulhona/tbecmodel_v2: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/Gunulhona/tbecmodel_v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Gunulhona/tbecmodel_v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Gunulhona/tbecmodel_v2/resolve/main/pytorch_model.bin
498 MB
- Xet hash:
- 5012b432abafd9ffdf480304e0f8db8f434b13dde2521a1fff9dbbbdc0eaf331
- Size of remote file:
- 498 MB
- SHA256:
- 67d2880a5876010c131a5a8f26be0884d0cbece0bb86d7e3884924781782d1ea
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