Instructions to use handraise-dev/3270_Miro-Dove with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use handraise-dev/3270_Miro-Dove with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="handraise-dev/3270_Miro-Dove")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("handraise-dev/3270_Miro-Dove") model = AutoModelForSequenceClassification.from_pretrained("handraise-dev/3270_Miro-Dove") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 054d5714b555a1069fbf46183cd6f69720186211ccde632d0a30054ac5279146
- Size of remote file:
- 4.92 kB
- SHA256:
- f24d59b2cb9197f9256ad1f2041d708af010a2908542291f4397bee8a60f4158
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