Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use EgorSys/students_scores_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EgorSys/students_scores_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EgorSys/students_scores_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EgorSys/students_scores_model") model = AutoModelForSequenceClassification.from_pretrained("EgorSys/students_scores_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9b4a2b25a4d1d09060f38a32e0f6f85b50b304658592cb082bfec3c7324a8f8
- Size of remote file:
- 5.37 kB
- SHA256:
- 1d5b1a33c7df0a7af19605082d85017301392988fb622585214cc6da97702489
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