Instructions to use hf-internal-testing/tiny-random-speech-encoder-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-speech-encoder-decoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-internal-testing/tiny-random-speech-encoder-decoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-speech-encoder-decoder") model = AutoModelForSpeechSeq2Seq.from_pretrained("hf-internal-testing/tiny-random-speech-encoder-decoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from hf-internal-testing/tiny-random-speech-encoder-decoder: direct link, hf CLI and curl.
- Browser
- Download file 564 Bytes
-
https://huggingface.co/hf-internal-testing/tiny-random-speech-encoder-decoder/resolve/7359e5cf0073bafda9a7fb46527acd46e7871202/tokenizer_config.json
- Command line
-
hf download hf://hf-internal-testing/tiny-random-speech-encoder-decoder@7359e5cf0073bafda9a7fb46527acd46e7871202/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/hf-internal-testing/tiny-random-speech-encoder-decoder/resolve/7359e5cf0073bafda9a7fb46527acd46e7871202/tokenizer_config.json
564 Bytes
| {"do_lower_case": false, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "tokenizer_file": "/home/ubuntu/.cache/huggingface/transformers/226a307193a9f4344264cdc76a12988448a25345ba172f2c7421f3b6810fddad.3dab63143af66769bbb35e3811f75f7e16b2320e12b7935e216bd6159ce6d9a6", "name_or_path": "bert-base-cased", "tokenizer_class": "BertTokenizer"} |