Instructions to use procit007/Classification_Model_v0.1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use procit007/Classification_Model_v0.1.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="procit007/Classification_Model_v0.1.0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("procit007/Classification_Model_v0.1.0") model = AutoModelForSequenceClassification.from_pretrained("procit007/Classification_Model_v0.1.0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d1ededdb88466140608a94ee5acc28db74e65ed2ff096a8c3992b868de6957a
- Size of remote file:
- 468 MB
- SHA256:
- 3e9dfec6e518d0240af9eeedc1dc25ce01a0b7367eb785bed3b0f83df4a0e514
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