Text Classification
Transformers
TensorBoard
Safetensors
English
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use srvmishra832/github_issues-dataset-distilbert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srvmishra832/github_issues-dataset-distilbert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="srvmishra832/github_issues-dataset-distilbert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("srvmishra832/github_issues-dataset-distilbert-base-uncased") model = AutoModelForSequenceClassification.from_pretrained("srvmishra832/github_issues-dataset-distilbert-base-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2d8c33dbacf9d5df45edf3f6b2584c9c6cfb8e87995cb131fd2ebfcee93b4df
- Size of remote file:
- 5.43 kB
- SHA256:
- 34488c6bc0280d59955040cc8d489a53c87e88678050024e056b6f1ff299b107
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