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Running
on
Zero
Running
on
Zero
use_wandb: False | |
dataset: | |
name: 'dataset' | |
records_path: null | |
initial_dataset: '' | |
label_schema: ["Yes", "No"] | |
max_samples: 10 | |
semantic_sampling: False # Change to True in case you don't have M1. Currently there is an issue with faiss and M1 | |
annotator: | |
method : 'argilla' | |
config: | |
api_url: 'https://kenken999-arglira.hf.space' | |
api_key: '12345678' | |
workspace: 'team' | |
time_interval: 5 | |
predictor: | |
method : 'llm' | |
config: | |
llm: | |
type: 'OpenAI' | |
name: 'llama3-70b-8192' | |
# async_params: | |
# retry_interval: 10 | |
# max_retries: 2 | |
model_kwargs: {"seed": 220} | |
num_workers: 5 | |
prompt: 'prompts/predictor_completion/prediction.prompt' | |
mini_batch_size: 1 #change to >1 if you want to include multiple samples in the one prompt | |
mode: 'prediction' | |
meta_prompts: | |
folder: 'prompts/meta_prompts_classification' | |
num_err_prompt: 1 # Number of error examples per sample in the prompt generation | |
num_err_samples: 2 # Number of error examples per sample in the sample generation | |
history_length: 4 # Number of sample in the meta-prompt history | |
num_generated_samples: 10 # Number of generated samples at each iteration | |
num_initialize_samples: 10 # Number of generated samples at iteration 0, in zero-shot case | |
samples_generation_batch: 10 # Number of samples generated in one call to the LLM | |
num_workers: 5 #Number of parallel workers | |
warmup: 4 # Number of warmup steps | |
eval: | |
function_name: 'accuracy' | |
num_large_errors: 4 | |
num_boundary_predictions : 0 | |
error_threshold: 0.5 | |
llm: | |
type: 'OpenAI' | |
name: 'llama3-70b-8192' | |
temperature: 0.8 | |
stop_criteria: | |
max_usage: 2 #In $ in case of OpenAI models, otherwise number of tokens | |
patience: 10 # Number of patience steps | |
min_delta: 0.01 # Delta for the improvement definition | |