Instructions to use mp6kv/pump_intent_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mp6kv/pump_intent_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mp6kv/pump_intent_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mp6kv/pump_intent_test") model = AutoModelForSequenceClassification.from_pretrained("mp6kv/pump_intent_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 968255df36d412ce897f26539979dd021975b76bd8f0715d333f27dd8a858e85
- Size of remote file:
- 499 MB
- SHA256:
- 47dc9e344ff9074322d4a8fece22db1ef0a3df4de22191be5b50218ef81c6eed
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