Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use epicmobile181/huggingface_sequence_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use epicmobile181/huggingface_sequence_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="epicmobile181/huggingface_sequence_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("epicmobile181/huggingface_sequence_classification") model = AutoModelForSequenceClassification.from_pretrained("epicmobile181/huggingface_sequence_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from epicmobile181/huggingface_sequence_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/epicmobile181/huggingface_sequence_classification/resolve/refs%2Fpr%2F2/training_args.bin
- Command line
-
hf download hf://epicmobile181/huggingface_sequence_classification@refs/pr/2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/epicmobile181/huggingface_sequence_classification/resolve/refs%2Fpr%2F2/training_args.bin
4.03 kB
- Xet hash:
- 1f4abcd5cb48fa300cd1168e1c58a051371bd717fb6f868d24d8bd49bdb09f68
- Size of remote file:
- 4.03 kB
- SHA256:
- 4eadf7a70aec24fad68f5cd0a5253a30416e24be28a617fa9e4478087273d157
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