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import os | |
import torch | |
from huggingface_hub import HfApi | |
# replace this with our token | |
TOKEN = os.environ.get("HF_TOKEN", None) | |
# print(TOKEN) | |
# OWNER = "vectara" | |
# REPO_ID = f"{OWNER}/Humanlike" | |
# QUEUE_REPO = f"{OWNER}/requests" | |
# RESULTS_REPO = f"{OWNER}/results" | |
OWNER = "Simondon" # Change to your org - don't forget to create a results and request dataset, with the correct format! | |
# ---------------------------------- | |
REPO_ID = f"{OWNER}/Humanlike" | |
QUEUE_REPO = f"{OWNER}/requests" | |
RESULTS_REPO = f"{OWNER}/results" | |
# print(RESULTS_REPO) | |
CACHE_PATH=os.getenv("HF_HOME", ".") | |
# Local caches | |
EVAL_REQUESTS_PATH = os.path.join(CACHE_PATH, "eval-queue") | |
EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-results") | |
EVAL_REQUESTS_PATH_BACKEND = os.path.join(CACHE_PATH, "eval-queue-bk") | |
EVAL_RESULTS_PATH_BACKEND = os.path.join(CACHE_PATH, "eval-results-bk") | |
# print(EVAL_RESULTS_PATH) | |
# exit() | |
DEVICE = torch.device('cuda' if torch.cuda.is_available() else 'cpu') #"cpu" | |
API = HfApi(token=TOKEN) | |
DATASET_PATH = "./src/datasets/Material_Llama2_0603.xlsx" #experiment data | |
PROMPT_PATH = "./src/datasets/prompt.xlsx" #prompt for each experiment | |
HEM_PATH = 'vectara/hallucination_evaluation_model' | |
HUMAN_DATA = "./src/datasets/human_data.csv" #experiment data | |
ITEM_4_DATA = "./src/datasets/associataion_dataset.csv" #database | |
ITEM_5_DATA = "./src/datasets/Items_5.csv" #experiment 5 need verb words | |
# SYSTEM_PROMPT = "You are a chat bot answering questions using data. You must stick to the answers provided solely by the text in the passage provided." | |
SYSTEM_PROMPT = "You are a participant of a psycholinguistic experiment. You will do a task on English language use." | |
'''prompt''' | |
# USER_PROMPT = "You are asked the question 'Provide a concise summary of the following passage, covering the core pieces of information described': " | |
USER_PROMPT = "" |