Instructions to use ZarahShibli/pharo-code-comment-classification3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZarahShibli/pharo-code-comment-classification3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ZarahShibli/pharo-code-comment-classification3")# Load model directly from transformers import AutoTokenizer, BERTClass tokenizer = AutoTokenizer.from_pretrained("ZarahShibli/pharo-code-comment-classification3") model = BERTClass.from_pretrained("ZarahShibli/pharo-code-comment-classification3") - Notebooks
- Google Colab
- Kaggle
File size: 658 Bytes
e76750d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"_name_or_path": "bert-base-uncased",
"architectures": [
"BERTClass"
],
"attention_probs_dropout_prob": 0.1,
"classifier_dropout": null,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "bert",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 0,
"position_embedding_type": "absolute",
"torch_dtype": "float32",
"transformers_version": "4.36.0",
"type_vocab_size": 2,
"use_cache": true,
"vocab_size": 30522
}
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