Text Classification
Transformers
Safetensors
Arabic
bert
feature-extraction
arabic
dialect-identification
arabic-dialects
msa
encoder
tiny-model
text-embeddings-inference
Instructions to use oddadmix/Nawah-Dialect-BERT-6M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oddadmix/Nawah-Dialect-BERT-6M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="oddadmix/Nawah-Dialect-BERT-6M")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("oddadmix/Nawah-Dialect-BERT-6M") model = AutoModel.from_pretrained("oddadmix/Nawah-Dialect-BERT-6M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from oddadmix/Nawah-Dialect-BERT-6M: direct link, hf CLI and curl.
- Browser
- Download file 1.12 kB
-
https://huggingface.co/oddadmix/Nawah-Dialect-BERT-6M/resolve/main/config.json
- Command line
-
hf download hf://oddadmix/Nawah-Dialect-BERT-6M/config.json
-
curl -L -o config.json https://huggingface.co/oddadmix/Nawah-Dialect-BERT-6M/resolve/main/config.json
1.12 kB
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "BertModel" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 128, | |
| "id2label": { | |
| "0": "bh", | |
| "1": "dz", | |
| "2": "eg", | |
| "3": "iq", | |
| "4": "lb", | |
| "5": "ly", | |
| "6": "ma", | |
| "7": "msa", | |
| "8": "ps", | |
| "9": "sa", | |
| "10": "sd", | |
| "11": "sy", | |
| "12": "tn", | |
| "13": "ye" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 512, | |
| "is_decoder": false, | |
| "label2id": { | |
| "bh": 0, | |
| "dz": 1, | |
| "eg": 2, | |
| "iq": 3, | |
| "lb": 4, | |
| "ly": 5, | |
| "ma": 6, | |
| "msa": 7, | |
| "ps": 8, | |
| "sa": 9, | |
| "sd": 10, | |
| "sy": 11, | |
| "tn": 12, | |
| "ye": 13 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 2048, | |
| "model_type": "bert", | |
| "num_attention_heads": 2, | |
| "num_hidden_layers": 8, | |
| "pad_token_id": 1, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.15.1", | |
| "type_vocab_size": 2, | |
| "use_cache": false, | |
| "vocab_size": 32000, | |
| "num_labels": 14 | |
| } |