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  • FastChat fastchat llm_judge gen_model_answer. py at main - GitHub
    Usage: python3 gen_model_answer py --model-path lmsys fastchat-t5-3b-v1 0 --model-id fastchat-t5-3b-v1 0 """ import argparse import json import os import random import time import shortuuid import torch from tqdm import tqdm from fastchat llm_judge common import load_questions, temperature_config from fastchat model import load_model, get
  • FastChat fastchat llm_judge common. py at main · lm-sys FastChat
    questions = [] with open (question_file, "r") as ques_file: for line in ques_file: if line: questions append (json loads (line)) questions = questions [begin:end] return questions def load_model_answers (answer_dir: str):
  • evalchemy eval chat_benchmarks MTBench fastchat llm_judge common. py at main . . . - GitHub
    The return value is a python dict of type: Dict [judge_name: str -> dict] """ prompts = {} with open (prompt_file) as fin: for line in fin: line = json loads (line) prompts [line ["name"]] = line return prompts def run_judge_single (question, answer, judge, ref_answer, multi_turn=False): kwargs = {} model = judge model_name if ref_answer is not
  • ChatPsychiatrist fastchat llm_judge gen_model_answer. py at master · EmoCareAI . . .
    Usage: python3 gen_model_answer py --model-path lmsys fastchat-t5-3b-v1 0 --model-id fastchat-t5-3b-v1 0 """ import argparse import json import os import random import time import shortuuid import torch from tqdm import tqdm from fastchat llm_judge common import load_questions, temperature_config from fastchat model import load_model, get
  • evalchemy eval chat_benchmarks MTBench fastchat llm_judge gen_api_answer. py at main . . .
    """Generate answers with GPT-4 Usage: python3 gen_api_answer py --model gpt-3 5-turbo """ import argparse import json import os import time import concurrent futures import openai import shortuuid import tqdm from fastchat llm_judge common import ( load_questions, temperature_config, chat_completion_openai, chat_completion_anthropic, chat
  • Support package-data for llm_judge · Issue #3199 · lm-sys FastChat - GitHub
    It seems better to ensure that data for llm_judge is included in the package, even if installed via pip Install with pip pip3 install "fschat [model_worker,llm_judge]" Script for using llm_judge as module python3 -m fastchat llm_judge ge
  • ChatPsychiatrist fastchat llm_judge README. md at master - GitHub
    In this package, you can use MT-bench questions and prompts to evaluate your models with LLM-as-a-judge MT-bench is a set of challenging multi-turn open-ended questions for evaluating chat assistants To automate the evaluation process, we prompt strong LLMs like GPT-4 to act as judges and assess the quality of the models' responses
  • evalchemy eval chat_benchmarks MTBench fastchat llm_judge gen_judgment. py at main . . .
    Only run the first `n` judgments ") args = parser parse_args () question_file = f"data {args bench_name} question jsonl" answer_dir = f"data {args bench_name} model_answer" ref_answer_dir = f"data {args bench_name} reference_answer" # Load questions questions = load_questions (question_file, None, None) # Load answers model_answers = load
  • MoA generate_for_mt_bench. py at main - GitHub
    Usage: python3 gen_model_answer py --model-path lmsys fastchat-t5-3b-v1 0 --model-id fastchat-t5-3b-v1 0 """ import argparse import json import os import random import time import shortuuid import torch from tqdm import tqdm from fastchat llm_judge common import load_questions, temperature_config from fastchat model import load_model, get
  • ChatPsychiatrist fastchat llm_judge qa_browser. py at master · EmoCareAI . . . - GitHub
    """ Usage: python3 qa_browser py --share """ import argparse from collections import defaultdict import re import gradio as gr from fastchat llm_judge common import ( load_questions, load_model_answers, load_single_model_judgments, load_pairwise_model_judgments, resolve_single_judgment_dict, resolve_pairwise_judgment_dict, get_single_judge
  • Issue #2657 · lm-sys FastChat - GitHub
    Successfully merging a pull request may close this issue Hello - it appears that the new openai client library released this week breaks the MT-bench evaluation script (test-env) rshaw@gpuprod:~ FastChat fastchat llm_judge$ python gen_judgment py --model-list claude-v1 gpt-3 5-turbo --parallel
  • ChatPsychiatrist fastchat llm_judge gen_api_answer. py at master · EmoCareAI . . . - GitHub
    """Generate answers with GPT-4 Usage: python3 get_api_answer py --model gpt-3 5-turbo """ import argparse import json import os import time import concurrent futures import shortuuid import tqdm from fastchat llm_judge common import ( load_questions, temperature_config, chat_compeletion_openai, chat_compeletion_anthropic, chat_compeletion_palm





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