Instructions to use hf-tiny-model-private/tiny-random-Speech2TextForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-Speech2TextForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-tiny-model-private/tiny-random-Speech2TextForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-Speech2TextForConditionalGeneration") model = AutoModelForSpeechSeq2Seq.from_pretrained("hf-tiny-model-private/tiny-random-Speech2TextForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
File size: 557 Bytes
5a64e5d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"bos_token": "<s>",
"clean_up_tokenization_spaces": true,
"do_lower_case": true,
"do_upper_case": false,
"eos_token": "</s>",
"lang_codes": null,
"model_max_length": 20,
"pad_token": "<pad>",
"sp_model_kwargs": {},
"special_tokens_map_file": "/home/suraj/.cache/huggingface/transformers/f39f1499e9c4d2b3e803e3cad8a31c4cf3e626e1c69197d4cd6921e5c07007f9.9d6cd81ef646692fb1c169a880161ea1cb95f49694f220aced9b704b457e51dd",
"tgt_lang": null,
"tokenizer_class": "Speech2TextTokenizer",
"tokenizer_file": null,
"unk_token": "<unk>"
}
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