Instructions to use ivanlau/distil-bert-uncased-finetuned-github-issues with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ivanlau/distil-bert-uncased-finetuned-github-issues with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ivanlau/distil-bert-uncased-finetuned-github-issues")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ivanlau/distil-bert-uncased-finetuned-github-issues") model = AutoModelForSequenceClassification.from_pretrained("ivanlau/distil-bert-uncased-finetuned-github-issues", device_map="auto") - Notebooks
- Google Colab
- Kaggle
added code section to readme file
Browse files
readme.md
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@@ -14,4 +14,7 @@ The following hyperparameters were used during training:
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- optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 0
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- num_epochs: 5
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- optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 0
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- num_epochs: 5
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### Codes
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https://github.com/IvanLauLinTiong/IntelliLabel
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