Text Classification
Transformers
Safetensors
Hebrew
bert
intent-classification
hebrew
alephbert
shopping
text-embeddings-inference
Instructions to use spivi87/alephbert-intent-he with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spivi87/alephbert-intent-he with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="spivi87/alephbert-intent-he")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("spivi87/alephbert-intent-he") model = AutoModelForSequenceClassification.from_pretrained("spivi87/alephbert-intent-he") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "BertForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": null, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": null, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "GROCERY_REQUEST", | |
| "1": "RECIPE_URL", | |
| "2": "LIST_QUERY", | |
| "3": "CLEAR_LIST", | |
| "4": "REMOVE_ITEM", | |
| "5": "PARTIAL_COMPLETION", | |
| "6": "GROUP_INFO", | |
| "7": "GET_INVITE_CODE", | |
| "8": "CREATE_INVITE", | |
| "9": "RENAME_GROUP", | |
| "10": "LEAVE_GROUP", | |
| "11": "NOTIFICATION_SETTINGS", | |
| "12": "REVOKE_INVITE", | |
| "13": "RECIPE_SEARCH", | |
| "14": "UPDATE_QUANTITY", | |
| "15": "BUG_REPORT", | |
| "16": "OTHER" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "label2id": { | |
| "BUG_REPORT": 15, | |
| "CLEAR_LIST": 3, | |
| "CREATE_INVITE": 8, | |
| "GET_INVITE_CODE": 7, | |
| "GROCERY_REQUEST": 0, | |
| "GROUP_INFO": 6, | |
| "LEAVE_GROUP": 10, | |
| "LIST_QUERY": 2, | |
| "NOTIFICATION_SETTINGS": 11, | |
| "OTHER": 16, | |
| "PARTIAL_COMPLETION": 5, | |
| "RECIPE_SEARCH": 13, | |
| "RECIPE_URL": 1, | |
| "REMOVE_ITEM": 4, | |
| "RENAME_GROUP": 9, | |
| "REVOKE_INVITE": 12, | |
| "UPDATE_QUANTITY": 14 | |
| }, | |
| "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", | |
| "problem_type": "single_label_classification", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.9.0", | |
| "type_vocab_size": 1, | |
| "use_cache": false, | |
| "vocab_size": 52000 | |
| } | |