Instructions to use deprem-ml/intent_128k_v13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deprem-ml/intent_128k_v13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="deprem-ml/intent_128k_v13", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("deprem-ml/intent_128k_v13") model = AutoModelForSequenceClassification.from_pretrained("deprem-ml/intent_128k_v13", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ecce707b8eeb0ec76cb72355603241dcda8aad19c32142d8372d077cb80a3f9
- Size of remote file:
- 1.47 GB
- SHA256:
- fc2868d5a8db714ebf9d0d572968b75fe0ece92f8abfeaa804d6989a54df4dcf
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