Instructions to use ChillingDream/dap-mbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChillingDream/dap-mbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ChillingDream/dap-mbert-base")# Load model directly from transformers import AutoTokenizer, BertForRLM tokenizer = AutoTokenizer.from_pretrained("ChillingDream/dap-mbert-base") model = BertForRLM.from_pretrained("ChillingDream/dap-mbert-base") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "/mnt/bingadseuunifiedstorage/v-liziheng/result/xtreme-rlm-t2-target-enlm-fwd-ams0-bert-base-multilingual-cased.2", | |
| "architectures": [ | |
| "BertForRLM" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "directionality": "bidi", | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "langs": [ | |
| "af", | |
| "ar", | |
| "bg", | |
| "bn", | |
| "de", | |
| "el", | |
| "es", | |
| "et", | |
| "eu", | |
| "fa", | |
| "fi", | |
| "fr", | |
| "he", | |
| "hi", | |
| "hu", | |
| "id", | |
| "it", | |
| "ja", | |
| "jv", | |
| "ka", | |
| "kk", | |
| "ko", | |
| "ml", | |
| "mr", | |
| "nl", | |
| "pt", | |
| "ru", | |
| "sw", | |
| "ta", | |
| "te", | |
| "th", | |
| "tl", | |
| "tr", | |
| "ur", | |
| "vi", | |
| "zh" | |
| ], | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "n_langs": 38, | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "position_embedding_type": "absolute", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.20.1", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "use_lang_emb": false, | |
| "vocab_size": 119547 | |
| } | |