Instructions to use mp6kv/main_intent_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mp6kv/main_intent_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mp6kv/main_intent_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mp6kv/main_intent_test") model = AutoModelForSequenceClassification.from_pretrained("mp6kv/main_intent_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12b48ace400116f3bdffc1684eee8dd9ce597391b9854e512660ca212cde33ed
- Size of remote file:
- 499 MB
- SHA256:
- 9b878a8d77c255a9ed6e6f3bf9a7b757b2afbd8443c66d38c6a02bb31e54ef27
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.