Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use at2507/finetuned_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use at2507/finetuned_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="at2507/finetuned_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("at2507/finetuned_model") model = AutoModelForSequenceClassification.from_pretrained("at2507/finetuned_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from at2507/finetuned_model: direct link, hf CLI and curl.
- Browser
- Download file 669 kB
-
https://huggingface.co/at2507/finetuned_model/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://at2507/finetuned_model@refs/pr/2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/at2507/finetuned_model/resolve/refs%2Fpr%2F2/tokenizer.json
669 kB
File too large to display, you can check the raw version instead.