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Runtime error
| from transformers import pipeline | |
| import streamlit as st | |
| import torch | |
| device = "cuda:0" if torch.cuda.is_available() else "cpu" | |
| pipe = pipeline('LLaVA', model='liuhaotian/llava-v1.5-13b', device=device ) | |
| text = st.text_area('Enter some text here!') | |
| if text: | |
| out = pipe(text) | |
| st.json(out) | |
| # from transformers import pipeline | |
| # import torch | |
| # device = "cuda:0" if torch.cuda.is_available() else "cpu" | |
| # classifier = pipeline( | |
| # "audio-classification", model="MIT/ast-finetuned-speech-commands-v2", device=device | |
| # ) | |
| # from transformers.pipelines.audio_utils import ffmpeg_microphone_live | |
| # def launch_fn( | |
| # wake_word="marvin", | |
| # prob_threshold=0.5, | |
| # chunk_length_s=2.0, | |
| # stream_chunk_s=1, | |
| # debug=False, | |
| # ): | |
| # if wake_word not in classifier.model.config.label2id.keys(): | |
| # raise ValueError( | |
| # f"Wake word {wake_word} not in set of valid class labels, pick a wake word in the set {classifier.model.config.label2id.keys()}." | |
| # ) | |
| # sampling_rate = classifier.feature_extractor.sampling_rate | |
| # mic = ffmpeg_microphone_live( | |
| # sampling_rate=sampling_rate, | |
| # chunk_length_s=chunk_length_s, | |
| # stream_chunk_s=stream_chunk_s, | |
| # ) | |
| # print("Listening for wake word...") | |
| # mic_results = classifier(mic) | |
| # for prediction in mic_results: | |
| # prediction = prediction[0] | |
| # if debug: | |
| # print(prediction) | |
| # if prediction["label"] == wake_word: | |
| # if prediction["score"] > prob_threshold: | |
| # return True | |
| # launch_fn(debug=True) | |