Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Rami/multi-label-class-classification-on-github-issues with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rami/multi-label-class-classification-on-github-issues with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Rami/multi-label-class-classification-on-github-issues")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Rami/multi-label-class-classification-on-github-issues") model = AutoModelForSequenceClassification.from_pretrained("Rami/multi-label-class-classification-on-github-issues") - Inference
- Notebooks
- Google Colab
- Kaggle
Upload VID_20260411_054557_149.mp3
#3 opened about 1 month ago
by
Nnwa6548
Librarian Bot: Add base_model information to model
#2 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#1 opened about 3 years ago
by
SFconvertbot