Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use sk01/DataFeed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sk01/DataFeed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sk01/DataFeed")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sk01/DataFeed") model = AutoModelForSequenceClassification.from_pretrained("sk01/DataFeed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sk01/DataFeed: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/sk01/DataFeed/resolve/refs%2Fpr%2F2/training_args.bin
- Command line
-
hf download hf://sk01/DataFeed@refs/pr/2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sk01/DataFeed/resolve/refs%2Fpr%2F2/training_args.bin
3.52 kB
- Xet hash:
- bdcce073a0f8de1a04a89698e6ca084673b92ed3480d0c9b65991a3ddedfd22d
- Size of remote file:
- 3.52 kB
- SHA256:
- 06876e21f3e56fbf94a312b4e718cf0c2432363534cb90ebbf03fce74bc1aad7
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