Instructions to use smerchi/text_classification_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smerchi/text_classification_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="smerchi/text_classification_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("smerchi/text_classification_2") model = AutoModelForSequenceClassification.from_pretrained("smerchi/text_classification_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b76d3e887e4a91225a2ec2df086376e3a7777001ba1dc097e7fb74701954b95
- Size of remote file:
- 541 MB
- SHA256:
- e00b7a20c93f2534e394009443fee83164f32ca1e68f76d9d9d2228ea190c224
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