Instructions to use giganticode/StackOBERTflow-comments-small-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use giganticode/StackOBERTflow-comments-small-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="giganticode/StackOBERTflow-comments-small-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("giganticode/StackOBERTflow-comments-small-v1") model = AutoModelForMaskedLM.from_pretrained("giganticode/StackOBERTflow-comments-small-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bfe78eea312d61ae22affcde93cff849af1bae8a78879b7084300d4472604a1e
- Size of remote file:
- 336 MB
- SHA256:
- fe20651a25a129c4a2a985d3f4006fe72b8bee517b4f9fb3f36a2aba133bd576
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