Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use anth0nyhak1m/SS_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anth0nyhak1m/SS_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anth0nyhak1m/SS_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anth0nyhak1m/SS_model") model = AutoModelForSequenceClassification.from_pretrained("anth0nyhak1m/SS_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5be1176653fb143bb5ccdb7780e36cadfcac682600842d5fac51769c5e423a1e
- Size of remote file:
- 268 MB
- SHA256:
- 86fc525b499453d31fa36e361165392a9b242f4f6d669385241958bb6461d92c
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