Instructions to use KamrusSamad/bnbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KamrusSamad/bnbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="KamrusSamad/bnbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("KamrusSamad/bnbert") model = AutoModelForMaskedLM.from_pretrained("KamrusSamad/bnbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from KamrusSamad/bnbert: direct link, hf CLI and curl.
- Browser
- Download file 931 Bytes
-
https://huggingface.co/KamrusSamad/bnbert/resolve/main/config.json
- Command line
-
hf download hf://KamrusSamad/bnbert/config.json
-
curl -L -o config.json https://huggingface.co/KamrusSamad/bnbert/resolve/main/config.json
931 Bytes
| { | |
| "_name_or_path": "ckiplab/albert-tiny-chinese", | |
| "architectures": [ | |
| "BertForMaskedLM" | |
| ], | |
| "attention_probs_dropout_prob": 0.0, | |
| "bos_token_id": 101, | |
| "classifier_dropout": null, | |
| "classifier_dropout_prob": 0.1, | |
| "down_scale_factor": 1, | |
| "embedding_size": 128, | |
| "eos_token_id": 102, | |
| "gap_size": 0, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.0, | |
| "hidden_size": 312, | |
| "initializer_range": 0.02, | |
| "inner_group_num": 1, | |
| "intermediate_size": 1248, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "net_structure_type": 0, | |
| "num_attention_heads": 12, | |
| "num_hidden_groups": 1, | |
| "num_hidden_layers": 4, | |
| "num_memory_blocks": 0, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "tokenizer_class": "BertTokenizerFast", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.17.0", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 30522 | |
| } | |