Instructions to use 3FEET/M4T2-Signals with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 3FEET/M4T2-Signals with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="3FEET/M4T2-Signals")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("3FEET/M4T2-Signals") model = AutoModelForSequenceClassification.from_pretrained("3FEET/M4T2-Signals", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1bacef27ba1c83c1e260d8b6df68fbd7dff57c835699c89cfd1aca3a3356e724
- Size of remote file:
- 433 MB
- SHA256:
- 8c381edfd922007aa3e07ea3af1541d5e5c3842f4c0ee64934bbf758d941cfe3
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