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:
- 143ba90760b360326f88ff11dee3f78b6b051c8faf78c25b4e080445f0226e0b
- Size of remote file:
- 2.99 kB
- SHA256:
- 93bfccff881d1378d5cf8579a582f23d0e35b373e17df24b1e8ce1aab96917a9
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