Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use toasterboy/TESDFEEEE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toasterboy/TESDFEEEE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="toasterboy/TESDFEEEE")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("toasterboy/TESDFEEEE") model = AutoModelForSequenceClassification.from_pretrained("toasterboy/TESDFEEEE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from toasterboy/TESDFEEEE: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/toasterboy/TESDFEEEE/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://toasterboy/TESDFEEEE@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/toasterboy/TESDFEEEE/resolve/refs%2Fpr%2F2/pytorch_model.bin
436 MB
- Xet hash:
- 72a1f9af0a70ab6e8736c308d82296432deafd747c38c0292df42d75f68c15fa
- Size of remote file:
- 436 MB
- SHA256:
- 4ae7058f3c8c2d7df426d3e7b31ae147afe00d27ba06a033555ea055d6b5a2b7
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