Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use pglee/github-issue-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pglee/github-issue-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pglee/github-issue-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pglee/github-issue-classifier") model = AutoModelForSequenceClassification.from_pretrained("pglee/github-issue-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from pglee/github-issue-classifier: direct link, hf CLI and curl.
- Browser
- Download file 23 Bytes
-
https://huggingface.co/pglee/github-issue-classifier/resolve/refs%2Fpr%2F2/added_tokens.json
- Command line
-
hf download hf://pglee/github-issue-classifier@refs/pr/2/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/pglee/github-issue-classifier/resolve/refs%2Fpr%2F2/added_tokens.json
23 Bytes
| { | |
| "[MASK]": 128000 | |
| } | |