Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use smi-egor/students_scores_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smi-egor/students_scores_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="smi-egor/students_scores_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("smi-egor/students_scores_model") model = AutoModelForSequenceClassification.from_pretrained("smi-egor/students_scores_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from smi-egor/students_scores_model: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/smi-egor/students_scores_model/resolve/main/training_args.bin
- Command line
-
hf download hf://smi-egor/students_scores_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/smi-egor/students_scores_model/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 9db82728473dbc8524b35d498c1d80cf70a2cbbdb195955d29b910975438b609
- Size of remote file:
- 5.3 kB
- SHA256:
- 063852dde7c480fbaa285836528fd4224830d79c4da87beeaf126869d4a3a092
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