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Runtime error
File size: 1,596 Bytes
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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)
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