Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use sms112/euk_roberta_large_essentiality_Network with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sms112/euk_roberta_large_essentiality_Network with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sms112/euk_roberta_large_essentiality_Network")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sms112/euk_roberta_large_essentiality_Network") model = AutoModelForSequenceClassification.from_pretrained("sms112/euk_roberta_large_essentiality_Network") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e5cb6a77e6131b4b099df05627d0391b3817d94a2bab471bef712fc13785f56
- Size of remote file:
- 1.42 GB
- SHA256:
- bb66a7b3fbfa97aff87fd8a468d7f89bbd53cc4ea0f94080922823d95913ab06
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