How to use hf-tiny-model-private/tiny-random-SpeechEncoderDecoderModel-wav2vec2-bert 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-SpeechEncoderDecoderModel-wav2vec2-bert")
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-SpeechEncoderDecoderModel-wav2vec2-bert") model = AutoModelForSpeechSeq2Seq.from_pretrained("hf-tiny-model-private/tiny-random-SpeechEncoderDecoderModel-wav2vec2-bert", device_map="auto")
https://huggingface.co/hf-tiny-model-private/tiny-random-SpeechEncoderDecoderModel-wav2vec2-bert/resolve/498dde4320603286f0df9934c5086b8c056c9b3a/generation_config.json
hf download hf://hf-tiny-model-private/tiny-random-SpeechEncoderDecoderModel-wav2vec2-bert@498dde4320603286f0df9934c5086b8c056c9b3a/generation_config.json
curl -L -o generation_config.json https://huggingface.co/hf-tiny-model-private/tiny-random-SpeechEncoderDecoderModel-wav2vec2-bert/resolve/498dde4320603286f0df9934c5086b8c056c9b3a/generation_config.json
