Instructions to use CIIRC-NLP/alquistcoder-intention_recognition-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CIIRC-NLP/alquistcoder-intention_recognition-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CIIRC-NLP/alquistcoder-intention_recognition-final")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CIIRC-NLP/alquistcoder-intention_recognition-final") model = AutoModelForSequenceClassification.from_pretrained("CIIRC-NLP/alquistcoder-intention_recognition-final") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45375140d02bba3838cd1d53b138840d006a88d5152aab2982934f2779d6d8ec
- Size of remote file:
- 1.58 GB
- SHA256:
- a21a47e1e31f84a3ead003eee7088a474d249841e0154fce8f5fe35195e993d4
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