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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download .gitignore from Rami/multi-label-class-classification-on-github-issues: direct link, hf CLI and curl.
- Browser
- Download file 13 Bytes
-
https://huggingface.co/Rami/multi-label-class-classification-on-github-issues/resolve/main/.gitignore
- Command line
-
hf download hf://Rami/multi-label-class-classification-on-github-issues/.gitignore
-
curl -L -o .gitignore https://huggingface.co/Rami/multi-label-class-classification-on-github-issues/resolve/main/.gitignore
13 Bytes
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