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import os | |
import logging as log | |
log.basicConfig(level=log.INFO) | |
IMAGE_CAPTION_MODEL = "Salesforce/blip-image-captioning-large" | |
LLM_MODEL = "microsoft/Phi-3-mini-4k-instruct" | |
LLM_MAX_LENGTH = 50 | |
LLM_MAX_NEW_TOKENS = 50 | |
LLM_TEMPERATURE = 0.7 | |
LLM_TOP_P = 0.95 | |
MUSICGEN_MODEL = "facebook/musicgen-small" | |
MUSICGEN_MODEL_API_URL = f"https://api-inference.huggingface.co/models/{MUSICGEN_MODEL}" | |
MUSICGEN_MAX_NEW_TOKENS = 256 # 5 seconds of audio | |
AUDIO_DIR = "Case-Study-1/data/" | |
HF_API_TOKEN = os.getenv("HF_API_TOKEN") | |
if HF_API_TOKEN: | |
log.info(f"Read HF_API_TOKEN: {HF_API_TOKEN[0:4]}...") | |
else: | |
print("HF_API_TOKEN not found in environment variables.") | |
# ----ATTRIBUTION-START---- | |
# LLM: Github Copilot | |
# PROMPT: create an output folder for the generated audio files | |
# EDITS: / | |
def create_output_folder(): | |
os.makedirs(AUDIO_DIR, exist_ok=True) | |
# -----ATTRIBUTION-END----- | |
create_output_folder() | |