/
prometheus_config.yaml
38 lines (34 loc) · 1.09 KB
/
prometheus_config.yaml
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name: "lm-buddy-prometheus-job"
dataset:
# dataset stored as wandb artifact
path: "wandb://sample-entity/lm-buddy-examples/wandb-file-artifact:latest"
# dataset stored locally on disk
# path: "file:///path/to/hf_dataset_directory"
# field containing scoring instructions in the json file
text_field: "instruction"
prometheus:
inference:
base_url: "http://your.vllm.server:8000/v1"
# if you use llamafile and api_like_OAI.py,
# the base url will be the following one
# base_url: "http://localhost:8081/v1"
engine: "hf://kaist-ai/prometheus-13b-v1.0"
best_of: 1
max_tokens: 512
frequency_penalty: 1.03
temperature: 1.0
top_p: 0.9
evaluation:
# number of times a model is evaluated per sample
num_answers: 3
# max number of retries if a communication error
# with the server occurs
max_retries: 5
# scores as defined in the scoring rubric
scores: ["1", "2", "3", "4", "5"]
# enable/disable tqdm to track eval progress
enable_tqdm: True
# save evaluation results as a wandb artifact
tracking:
project: "lm-buddy-examples"
entity: "sample-entity"