Instructions to use AnuradhaPoddar/seq_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnuradhaPoddar/seq_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnuradhaPoddar/seq_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnuradhaPoddar/seq_classification") model = AutoModelForSequenceClassification.from_pretrained("AnuradhaPoddar/seq_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4585893b1e2894d12ac1320a51bac5787a234cee43568a2775583d2826275a2c
- Size of remote file:
- 1.63 GB
- SHA256:
- 9e400ec0c2726362f37ed13fa395bfca4d1a17326268c4805fa5b00e203056f5
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