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import os | |
INDEX_DIR = "data/index" | |
STATEMENTS_PATH = "data/statements.txt" | |
RETRIEVER_MODEL = "sentence-transformers/msmarco-distilbert-base-tas-b" | |
RETRIEVER_MODEL_FORMAT = "sentence_transformers" | |
RETRIEVER_TOP_K = 5 | |
# In HF Space, we use microsoft/deberta-v2-xlarge-mnli | |
# for local testing, a smaller model is better | |
NLI_MODEL = os.environ.get("NLI_MODEL", "valhalla/distilbart-mnli-12-1") | |
print(f"Used NLI model: {NLI_MODEL}") | |
# In HF Space, we use google/flan-t5-large | |
# for local testing, a smaller model is better | |
PROMPT_MODEL = os.environ.get("PROMPT_MODEL", "google/flan-t5-small") | |
print(f"Used Prompt model: {PROMPT_MODEL}") | |