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
Training in progress, epoch 1
Browse files- config.json +2 -2
- model.safetensors +2 -2
- runs/Dec06_12-13-27_d7de64af26e3/events.out.tfevents.1733487208.d7de64af26e3.23.1 +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -1
- training_args.bin +1 -1
- vocab.txt +0 -0
config.json
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{
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"_name_or_path": "bert-base-
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"architectures": [
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"BertForSequenceClassification"
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],
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"transformers_version": "4.47.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size":
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}
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"_name_or_path": "bert-base-uncased",
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"architectures": [
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"BertForSequenceClassification"
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],
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"transformers_version": "4.47.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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model.safetensors
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size 437970952
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runs/Dec06_12-13-27_d7de64af26e3/events.out.tfevents.1733487208.d7de64af26e3.23.1
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tokenizer.json
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tokenizer_config.json
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},
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"clean_up_tokenization_spaces": false,
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"cls_token": "[CLS]",
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"do_lower_case":
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"extra_special_tokens": {},
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"mask_token": "[MASK]",
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"model_max_length": 512,
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},
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"clean_up_tokenization_spaces": false,
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"extra_special_tokens": {},
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"mask_token": "[MASK]",
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"model_max_length": 512,
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training_args.bin
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vocab.txt
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