Instructions to use anyspeech/PhoneBERT-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anyspeech/PhoneBERT-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="anyspeech/PhoneBERT-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("anyspeech/PhoneBERT-tiny") model = AutoModelForMaskedLM.from_pretrained("anyspeech/PhoneBERT-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from anyspeech/PhoneBERT-tiny: direct link, hf CLI and curl.
- Browser
- Download file 686 Bytes
-
https://huggingface.co/anyspeech/PhoneBERT-tiny/resolve/main/config.json
- Command line
-
hf download hf://anyspeech/PhoneBERT-tiny/config.json
-
curl -L -o config.json https://huggingface.co/anyspeech/PhoneBERT-tiny/resolve/main/config.json
686 Bytes
| { | |
| "_name_or_path": "/scratch/lingjzhu_root/lingjzhu1/lingjzhu/PhoneBERT/bert-tiny/checkpoint-40000", | |
| "architectures": [ | |
| "BertForMaskedLM" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 384, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1536, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 514, | |
| "model_type": "bert", | |
| "num_attention_heads": 6, | |
| "num_hidden_layers": 4, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.30.0", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 450 | |
| } | |