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 training_args.bin from toasterboy/TESDFEEEE: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/toasterboy/TESDFEEEE/resolve/refs%2Fpr%2F2/training_args.bin
- Command line
-
hf download hf://toasterboy/TESDFEEEE@refs/pr/2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/toasterboy/TESDFEEEE/resolve/refs%2Fpr%2F2/training_args.bin
2.93 kB
- Xet hash:
- 113a08896cdba988eb882b6364aa3794fdeaa3d34258c232281caf86988cd96c
- Size of remote file:
- 2.93 kB
- SHA256:
- 9d9ad93e12ab39d3445ca60acc46b09a8551aa7336caffaa1db7a5301057a489
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