repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/serve/monitor/dataset_release_scripts/lmsys_chat_1m/filter_bad_conv.py | fastchat/serve/monitor/dataset_release_scripts/lmsys_chat_1m/filter_bad_conv.py | """
Filter conversations for release.
Dependency:
pip install opencc-python-reimplementedpip install opencc-python-reimplemented
Usage:
python3 filter_bad_conv_lmsys_chat_1m.py --in clean_battle_conv_20230630_tagged_v1_pii.json
"""
import argparse
from concurrent.futures import ProcessPoolExecutor
from collections im... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/serve/monitor/dataset_release_scripts/arena_33k/merge_field.py | fastchat/serve/monitor/dataset_release_scripts/arena_33k/merge_field.py | """Count the unique users in a battle log file."""
import argparse
import json
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--input", type=str)
parser.add_argument("--tag-file", type=str)
args = parser.parse_args()
# build index
objs = json.load(open(arg... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/serve/monitor/dataset_release_scripts/arena_33k/count_unique_users.py | fastchat/serve/monitor/dataset_release_scripts/arena_33k/count_unique_users.py | """Count the unique users in a battle log file."""
import argparse
import json
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--input", type=str)
args = parser.parse_args()
lines = json.load(open(args.input))
ct_anony_votes = 0
all_users = set()
all_mo... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/serve/monitor/dataset_release_scripts/arena_33k/upload_hf_dataset.py | fastchat/serve/monitor/dataset_release_scripts/arena_33k/upload_hf_dataset.py | """
Upload to huggingface.
"""
import json
from datasets import Dataset, DatasetDict, load_dataset
objs = json.load(open("clean_battle_conv_20230630_tagged_v3_pii_33k_added.json"))
data = Dataset.from_list(objs)
data.push_to_hub("lmsys/chatbot_arena_conversations", private=True)
| python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/serve/monitor/dataset_release_scripts/arena_33k/sample.py | fastchat/serve/monitor/dataset_release_scripts/arena_33k/sample.py | """
Count the unique users in a battle log file.
Usage:
python3 -input in.json --number 1000
"""
import argparse
import json
import random
K = 1000
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--input", type=str)
parser.add_argument("--number", type=int, nargs="+")
... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/serve/monitor/dataset_release_scripts/arena_33k/filter_bad_conv.py | fastchat/serve/monitor/dataset_release_scripts/arena_33k/filter_bad_conv.py | """
Filter conversations for release.
Usage: python3 filter_bad_conv.py --in clean_battle_conv_20230630_tagged_v1_pii.json
"""
import argparse
from collections import defaultdict
from enum import Enum, auto
import json
import os
import random
from tqdm import tqdm
BLOCKED_WORDS_FILENAME = "blocked_words.json"
blocke... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/serve/monitor/vote_time_stats/plot.py | fastchat/serve/monitor/vote_time_stats/plot.py | import json
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
infile = "output.jsonl"
date = "2024-03" # used in the plot
durations = []
with open(infile) as f:
for line in f:
data = json.loads(line)
l = data["left"]["finish"]
r = data["right"]["finish"]
v... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/serve/monitor/vote_time_stats/analyze_data.py | fastchat/serve/monitor/vote_time_stats/analyze_data.py | import datetime
import glob
import json
from collections import deque
import tqdm
def _serialize_json(data):
# Serialize JSON with sorted keys and no whitespace
return json.dumps(data, sort_keys=True, separators=(",", ":")).encode("utf-8")
types = {
"share",
"chat",
"flag",
"bothbad_vote",
... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/serve/monitor/classify/display_score.py | fastchat/serve/monitor/classify/display_score.py | import pandas as pd
import argparse
import os
from glob import glob
from sklearn.metrics import recall_score, precision_score
tag_names = {
"if_bench": ("if_v0.1", "if"),
"math_bench": ("math_v0.1", "math"),
"hard_bench": ("criteria_v0.1", "hard"),
"creative_writing_bench": ("creative_writing_v0.1", "c... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/serve/monitor/classify/label.py | fastchat/serve/monitor/classify/label.py | import argparse
import json
import pandas as pd
import os
import time
import concurrent.futures
import tqdm
import yaml
import random
import threading
import orjson
from category import Category
LOCK = threading.RLock()
TASKS = None
CACHE_DICT = None
OUTPUT_DICT = None
# API setting constants
API_MAX_RETRY = None
... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/serve/monitor/classify/category.py | fastchat/serve/monitor/classify/category.py | # Tag structure
# - category_tag
# - criteria_v0.1
# - specificity
# - ...
# - math_v0.1
# - math
# - if_v0.1
# - if
# - score
import ast
import re
class Category:
def __init__(self):
pass
@staticmethod
def create_category(name):
if name... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/protocol/api_protocol.py | fastchat/protocol/api_protocol.py | from typing import Literal, Optional, List, Dict, Any, Union
import time
import shortuuid
from pydantic import BaseModel, Field
class ErrorResponse(BaseModel):
object: str = "error"
message: str
code: int
class ModelPermission(BaseModel):
id: str = Field(default_factory=lambda: f"modelperm-{shortu... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/fastchat/protocol/openai_api_protocol.py | fastchat/protocol/openai_api_protocol.py | from typing import Literal, Optional, List, Dict, Any, Union
import time
import shortuuid
from pydantic import BaseModel, Field
class ErrorResponse(BaseModel):
object: str = "error"
message: str
code: int
class ModelPermission(BaseModel):
id: str = Field(default_factory=lambda: f"modelperm-{shortu... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/playground/__init__.py | playground/__init__.py | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false | |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/playground/benchmark/benchmark_api_provider.py | playground/benchmark/benchmark_api_provider.py | """
Usage:
python3 -m playground.benchmark.benchmark_api_provider --api-endpoint-file api_endpoints.json --output-file ./benchmark_results.json --random-questions metadata_sampled.json
"""
import argparse
import json
import time
import numpy as np
from fastchat.serve.api_provider import get_api_provider_stream_iter
f... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/playground/test_embedding/test_classification.py | playground/test_embedding/test_classification.py | import json
import os
import numpy as np
import openai
import pandas as pd
import requests
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report, accuracy_score
np.set_printoptions(threshold=10000)
def get_embeddin... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/playground/test_embedding/test_sentence_similarity.py | playground/test_embedding/test_sentence_similarity.py | import json
import os
import numpy as np
import openai
import requests
from scipy.spatial.distance import cosine
def get_embedding_from_api(word, model="vicuna-7b-v1.5"):
if "ada" in model:
resp = openai.Embedding.create(
model=model,
input=word,
)
embedding = np.a... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
lm-sys/FastChat | https://github.com/lm-sys/FastChat/blob/587d5cfa1609a43d192cedb8441cac3c17db105d/playground/test_embedding/test_semantic_search.py | playground/test_embedding/test_semantic_search.py | import json
import os
import numpy as np
import openai
import pandas as pd
import requests
from scipy.spatial.distance import cosine
def cosine_similarity(vec1, vec2):
try:
return 1 - cosine(vec1, vec2)
except:
print(vec1.shape, vec2.shape)
def get_embedding_from_api(word, model="vicuna-7b-... | python | Apache-2.0 | 587d5cfa1609a43d192cedb8441cac3c17db105d | 2026-01-04T14:41:02.114326Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/discord/verify-lobby.py | scripts/discord/verify-lobby.py | #!/usr/bin/env python3
"""This file is for moderators to verify new users in the lobby.
First, moderators read the brief introduction people write in the lobby.
If all people's introductions are acceptable, moderators run this script.
Needs BOT_TOKEN environment variable to be set to the bot token.
"""
import dis... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/discord/stats.py | scripts/discord/stats.py | #!/usr/bin/env python3
"""This file is for moderators to verify new users in the lobby.
First, moderators read the brief introduction people write in the lobby.
If all people's introductions are acceptable, moderators run this script.
Needs BOT_TOKEN environment variable to be set to the bot token.
"""
import dis... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/data_augment/data_augment.py | scripts/data_augment/data_augment.py | """Script for a variety of data augmentation techniques for generating Question answer pairs.
Depending on the class used it takes in the input files and generates summaries from essays (which then will result in a "write a story about [summary]"-> essay pair),#
buggs code (in order to have bugged code + "please fix" -... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/xor-codec/xor_codec.py | scripts/xor-codec/xor_codec.py | import gzip
import os
import shutil
import sys
from pathlib import Path
import numpy
def xor_uncompressed(dst, src_payload, src_base, block_size=4096):
fp_payload = open(src_payload, "rb")
fp_base = open(src_base, "rb")
with open(dst, "wb") as fp:
while True:
buf1 = numpy.array(bytear... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/data-collection/twitter/twitter_process_json.py | scripts/data-collection/twitter/twitter_process_json.py | # This file loops through compressed json tweet data, pre-processes them,
# and then extracts them into more unified parquet files that can be handed
# off for further processing. The main focus is on producing viable replies.
# Initial data exploration seems that there is no guarantee that the original
# tweets are i... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/data-collection/twitter/twitter_create_convs.py | scripts/data-collection/twitter/twitter_create_convs.py | import json
from pathlib import Path
import polars as pl
from tqdm import tqdm
# Sets up paths
# TODO: Source paths from env file
path_string = "PUT THE PATH HERE TO WHERE YOU STORED THE PARQUET FILES"
folder_path = Path(path_string)
processed_folder_path = folder_path / "processed"
output_path = folder_path / "twitt... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/postprocessing/regex_pii_detector.py | scripts/postprocessing/regex_pii_detector.py | import re
# Adapted from
# https://www.geeksforgeeks.org/how-to-validate-ssn-social-security-number-using-regular-expression/
# https://docs.opswat.com/mdcore/proactive-dlp/sample-regular-expressions
# https://github.com/m4ll0k/SecretFinder/blob/master/BurpSuite-SecretFinder/SecretFinder.py
regex_patterns = {
"go... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/postprocessing/task_schedule.py | scripts/postprocessing/task_schedule.py | from enum import Enum
import numpy as np
from scipy import optimize
class Task(Enum):
RANKING = 0
ANSWER = 1
PROMPT = 2
VOTE = 3
def task_selection(
num_ranking_tasks: int, current_prompts: int, target_num_prompts: int, p: float, answers_per_prompt: int
) -> Task:
"""
This computes whic... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/postprocessing/scoring.py | scripts/postprocessing/scoring.py | from dataclasses import dataclass, replace
from typing import Any
import numpy as np
import numpy.typing as npt
from scipy.stats import kendalltau
@dataclass
class Voter:
"""
Represents a single voter.
This tabulates the number of good votes, total votes,
and points.
We only put well-behaved peop... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/postprocessing/rankings.py | scripts/postprocessing/rankings.py | from typing import List
import numpy as np
def head_to_head_votes(ranks: List[List[int]]):
tallies = np.zeros((len(ranks[0]), len(ranks[0])))
names = sorted(ranks[0])
ranks = np.array(ranks)
# we want the sorted indices
ranks = np.argsort(ranks, axis=1)
for i in range(ranks.shape[1]):
... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/postprocessing/ranking_disagreement.py | scripts/postprocessing/ranking_disagreement.py | from collections import defaultdict
import numpy as np
import pandas as pd
import psycopg2
from rankings import ranked_pairs
from scipy.stats import kendalltau
# source: wikipedia ;)
# but here without the normalization
def normalised_kendall_tau_distance(values1, values2):
"""Compute the Kendall tau distance.""... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/postprocessing/importance_selection.py | scripts/postprocessing/importance_selection.py | import logging
import warnings
import numpy as np
import pandas as pd
import psycopg2
from scipy.optimize import LinearConstraint, minimize
from scipy.sparse import coo_array, csr_array, csr_matrix, hstack
from scipy.special import softmax
from tqdm import trange
from tqdm.contrib.logging import logging_redirect_tqdm
... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/postprocessing/infogain_selector.py | scripts/postprocessing/infogain_selector.py | import numpy as np
from scipy.special import gammaln, psi
from scipy.stats import dirichlet
'''
Legacy numerical solution.
Should not be used as it is probably broken
def make_range(*x):
"""
constructs leftover values for the simplex given the first k entries
(0,x_k) = 1-(x_1+...+x_(k-1))
"""
ret... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/scripts/frontend-development/find-missing-locales.py | scripts/frontend-development/find-missing-locales.py | import sys
from collections import defaultdict
from glob import glob
from json import load
from os import path
ALL_PATH = "../../website/public/locales/**/*.json"
DIR = path.dirname(__file__)
EN_PATH = "../../website/public/locales/en/*.json"
def get_not_translated(en_json, translation_json, parent_key=None):
no... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/pretokenizer/create_hf_tokenizer_config.py | model/pretokenizer/create_hf_tokenizer_config.py | import argparse
from distutils.util import strtobool as strtoboolint
import transformers
from tokenizer import build_tokenizer
from transformers.utils import cached_file
def strtobool(s: str) -> bool:
return bool(strtoboolint(s))
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/pretokenizer/pretokenize.py | model/pretokenizer/pretokenize.py | import argparse
import json
import random
from enum import IntEnum
from pathlib import Path
from subprocess import run
import indexed_dataset
import numpy as np
import torch
from model_training.custom_datasets.formatting import DatasetEntryLm, DatasetEntrySft, Role
from model_training.utils.utils import _strtobool, ge... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/pretokenizer/tokenizer.py | model/pretokenizer/tokenizer.py | # copied from https://github.com/epfLLM/Megatron-LLM/blob/main/megatron/tokenizer/tokenizer.py
# (only keeping _FalconTokenizer & _SentencePieceTokenizer)
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Megatron tokenizers."""
from abc import ABC, abstractmethod
def build_tokenizer(args):
"""... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/pretokenizer/indexed_dataset.py | model/pretokenizer/indexed_dataset.py | # copied from https://github.com/epfLLM/Megatron-LLM/blob/main/megatron/data/indexed_dataset.py
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# copied from fairseq/fairseq/data/indexed_d... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/metrics.py | model/model_training/metrics.py | import numpy as np
from scipy import stats as st
RM_METRICS = ["accuracy", "kendalltau", "spearmanr"]
def reward_accuracy(eval_pred):
logits = eval_pred.predictions
labels = eval_pred.label_ids
pos_scores, neg_scores = [], []
for b_logits, b_labels in zip(logits, labels):
b_labels = b_labels[... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/check_dataset_appearances.py | model/model_training/check_dataset_appearances.py | """
This script should help to detect any keywords or other unwanted appearances in the datasets
RUN WITH:
python check_dataset_appearances.py -d <datasets> --cache_dir <path-to-cache-dir> --mode <one of sft, rm, rl>
e.g.:
python check_dataset_appearances.py -d gpt4all webgpt --cache_dir .cache --mode sft
python chec... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/check_dataset_counts.py | model/model_training/check_dataset_counts.py | import argparse
from collections import Counter
from enum import Enum
from pathlib import Path
from typing import Any
import pandas as pd
import yaml
from langdetect import DetectorFactory, detect
from model_training.custom_datasets.formatting import DatasetEntrySft
from model_training.utils.utils import _strtobool, g... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/trainer_rl.py | model/model_training/trainer_rl.py | import argparse
import math
import os
import random
from argparse import Namespace
from typing import Sequence
import numpy as np
import torch
import transformers
import tritonclient.grpc as client_util
import trlx
from model_training.custom_datasets.formatting import QA_SPECIAL_TOKENS, format_pairs
from model_trainin... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/trainer_rm.py | model/model_training/trainer_rm.py | import argparse
import logging
import os
from typing import Callable, Literal, Optional, Sequence, Union
import datasets
import torch
from model_training.custom_datasets.ranking_collator import RankingDataCollator
from model_training.efficiency_utils import fuse_gelu
from model_training.metrics import RewardMetrics
fr... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/trainer_sft.py | model/model_training/trainer_sft.py | #!/usr/bin/env python3
import argparse
import logging
import os
from functools import partial
from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
import datasets
import torch
# from model_training.custom_datasets.formatting import DatasetEntry
from model_training.custom_datasets.dialogue_co... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/__init__.py | model/model_training/__init__.py | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false | |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/efficiency_utils.py | model/model_training/efficiency_utils.py | import functools
import torch
from transformers.activations import FastGELUActivation, GELUActivation, NewGELUActivation, QuickGELUActivation
def rsetattr(obj, attr, val):
pre, _, post = attr.rpartition(".")
return setattr(rgetattr(obj, pre) if pre else obj, post, val)
def rgetattr(obj, attr, *args):
d... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/to_triton.py | model/model_training/to_triton.py | import os
from argparse import Namespace
from string import Template
import torch
import transformers
from torch import nn
from trainer_rl import argument_parsing
from utils.utils import get_model
class SFTLogitsModel(nn.Module):
def __init__(self, model):
super().__init__()
self.model = model
... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tools/augment_oasst.py | model/model_training/tools/augment_oasst.py | """
Augment oasst dataset with sft generated results
You can use augment new response using a model with bad response, ie non SFT model
had to do this in a quick fashion, please tolerate the hackiness in the code
"""
import json
import os
# so far load_oasst_export is pretty deterministic in thread orde... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tools/model_chat.py | model/model_training/tools/model_chat.py | #!/usr/bin/env python3
"""
A very simple script to test model locally
"""
import argparse
from enum import Enum
from typing import List, Tuple
import torch
from model_training.custom_datasets.formatting import QA_SPECIAL_TOKENS
from model_training.utils.utils import _strtobool
from tokenizers import pre_tokenizers
... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tools/export_model.py | model/model_training/tools/export_model.py | import argparse
import sys
import model_training.models.reward_model # noqa: F401 make sure reward model is registered for AutoModel
import torch
from transformers import AutoModelForCausalLM, AutoModelForSequenceClassification, AutoTokenizer
def parse_args():
parser = argparse.ArgumentParser()
parser.add_a... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tools/sample_rm_data.py | model/model_training/tools/sample_rm_data.py | """
Recursive method to traverse down the conversation tree
Use fastlangid for language identification :
>> pip install fastlangid
"""
import glob
import json
import random
import sys
from collections import defaultdict
from copy import deepcopy
from fastlangid.langid import LID
langid = LID()
total_ran... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tools/check_oasst_export.py | model/model_training/tools/check_oasst_export.py | import argparse
from oasst_data import ExportMessageTree, read_message_tree_list, visit_messages_depth_first
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("input_file_path", type=str, help=".jsonl or jsonl.gz OA export")
parser.add_argument("--lang", type=str, help="comma separ... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tools/model_cli.py | model/model_training/tools/model_cli.py | #!/usr/bin/env python3
import argparse
import time
import torch
import transformers
from model_training.custom_datasets.formatting import QA_SPECIAL_TOKENS, format_pairs, format_system_prefix
from model_training.models import get_specific_model
from model_training.utils.utils import _strtobool
from tokenizers import p... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/extra_rm_datasets.py | model/model_training/custom_datasets/extra_rm_datasets.py | from model_training.custom_datasets.rank_datasets import AnthropicRLHF, HellaSwagDataset, SHPDataset
from torch.utils.data import Dataset
def load_anthropic_rlhf() -> tuple[Dataset, Dataset]:
train = AnthropicRLHF(split="train")
validation = AnthropicRLHF(split="test")
return train, validation
def load_... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/toxic_conversation.py | model/model_training/custom_datasets/toxic_conversation.py | """
SFT dataset to reject toxic questions
"""
import random
from datasets import load_dataset
from torch.utils.data import Dataset
class ProsocialDialogueExplaination(Dataset):
name = "explain_prosocial"
TEMPLATE = [
# 0 : reply or sentence of interest, 1 : reason of caution
("'{0}' Why ... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/pretrain_datasets.py | model/model_training/custom_datasets/pretrain_datasets.py | """
Datasets for LM objective pre-training aimed to prevent catastrophic forgetting during fine-tuning
"""
from pathlib import Path
from typing import Optional
from datasets import load_dataset
from model_training.custom_datasets.formatting import DatasetEntryLm
from torch.utils.data import Dataset
class Pretrain... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/oasst_dataset.py | model/model_training/custom_datasets/oasst_dataset.py | from pathlib import Path
from typing import Iterable, Literal, Optional
from model_training.custom_datasets.formatting import DatasetEntrySft, Role, Utterance
from oasst_data import ExportMessageNode, read_dataset_message_trees, read_message_trees, visit_threads_depth_first
from oasst_data.schemas import ExportMessage... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/qa_datasets.py | model/model_training/custom_datasets/qa_datasets.py | """
Open / close book QA datasets
"""
import glob
import json
import os
import random
import re
from collections import defaultdict
from pathlib import Path
from typing import Any
from urllib.request import urlopen
import numpy as np
import requests
from datasets import load_dataset
from model_training.custom_data... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/utils.py | model/model_training/custom_datasets/utils.py | # mostly taken from
# https://huggingface.co/datasets/gozfarb/ShareGPT_Vicuna_unfiltered/blob/main/optional_clean.py,
# https://huggingface.co/datasets/ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered/blob/main/wizardlm_clean.py
FILTER_BY_WORDS = [
"as a language model",
"as an AI language model",
"As... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/translation.py | model/model_training/custom_datasets/translation.py | """
List of translation dataset
GroNLP/divemt
fill in the blanks : https://huggingface.co/datasets/m_lama
"""
import random
from datasets import load_dataset
from torch.utils.data import Dataset
# postfix prompt
TRANSLATION_PROMPT = {
"zh": [ # simplified or any chinese which was not mentioned
... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/__init__.py | model/model_training/custom_datasets/__init__.py | """
High level functions for model training
"""
from typing import Optional
import numpy as np
from model_training.custom_datasets.extra_rm_datasets import load_anthropic_rlhf, load_hellaswag, load_shp
from model_training.custom_datasets.instruction import (
INSTRUCTION_DATASETS,
RAG_DATASETS,
Instruct... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/ranking_collator.py | model/model_training/custom_datasets/ranking_collator.py | from dataclasses import dataclass
from typing import Optional, Union
from model_training.custom_datasets.formatting import DatasetEntryRm
from transformers.tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTrainedTokenizerBase
from .formatting import format_pairs, format_reply
@dataclass
class Ranki... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/prompt_dialogue.py | model/model_training/custom_datasets/prompt_dialogue.py | import gzip
import json
import re
from pathlib import Path
from typing import List, Mapping, Optional, Sequence, Union
import requests
from datasets import load_dataset
from model_training.custom_datasets.formatting import DatasetEntrySft, Role, Utterance
from model_training.custom_datasets.oasst_dataset import ListDa... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/summarization.py | model/model_training/custom_datasets/summarization.py | """
Summarize different spectrum of documents
"""
import random
import numpy as np
from datasets import load_dataset
from torch.utils.data import Dataset
SUMMARIZATION_SPECIAL_TOKENS = {"Text": "", "Summary": ["TL;DR:", "Summarize this", "Give me the summary"]}
SUMMARY_SPECIAL_PROMPT = {
"multi_news": ["Summ... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/instruction.py | model/model_training/custom_datasets/instruction.py | """
These are in the form of 'INSTRUCTION', 'RESPONSE'
"""
import random
from typing import Optional
from datasets import load_dataset
from model_training.custom_datasets.formatting import DatasetEntry, create_dataset_entry_qa
from model_training.custom_datasets.utils import _filter_by_words
from torch.utils.data ... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/formatting.py | model/model_training/custom_datasets/formatting.py | import re
from enum import Enum
from itertools import zip_longest
from random import random, shuffle
from typing import Literal, Optional
from pydantic import BaseModel, validator
from pydantic.fields import ModelField
QA_SPECIAL_TOKENS = {
"Question": "<|prompter|>",
"Answer": "<|assistant|>",
"System": ... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/dialogue_collator.py | model/model_training/custom_datasets/dialogue_collator.py | import random
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
import torch
from model_training.custom_datasets.formatting import (
QA_SPECIAL_TOKENS,
DatasetEntryLm,
DatasetEntrySft,
format_pairs,
format_system_prefix,
)
from torch.nn import functional as F
f... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/custom_datasets/rank_datasets.py | model/model_training/custom_datasets/rank_datasets.py | import random
from collections import defaultdict
from typing import List
import numpy as np
from datasets import load_dataset
from torch.utils.data import Dataset
SEED = 2020
class SHPDataset(Dataset):
"""
Dataset class to load stanfordnlp/SHP for Reward Modeling
"""
name = "SHP"
def __init__... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tests/test_datasets.py | model/model_training/tests/test_datasets.py | from argparse import Namespace
import pytest
from model_training.custom_datasets import QA_DATASETS, SUMMARIZATION_DATASETS, get_one_dataset
from model_training.custom_datasets.dialogue_collator import DialogueDataCollator
from model_training.utils.utils import get_tokenizer
from torch.utils.data import ConcatDataset,... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tests/test_patched_gpt_neox.py | model/model_training/tests/test_patched_gpt_neox.py | import torch
from model_training.models.patching import patch_model
from transformers import AutoModelForCausalLM, AutoTokenizer, GPTNeoXModel
def test_flash_attention_patch(dtype=torch.float16, device="cuda"):
tokenizer = AutoTokenizer.from_pretrained("EleutherAI/pythia-70m-deduped")
tokenizer.add_special_to... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tests/test_oasst_dataset.py | model/model_training/tests/test_oasst_dataset.py | from argparse import Namespace
import pytest
from model_training.custom_datasets import get_one_dataset
@pytest.mark.skip(reason="cache not populated")
def test_load_oasst_export_dataset():
config = Namespace(
cache_dir=".cache",
)
kwargs = {
"lang": "en,es,de,fr",
"top_k": 2,
... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tests/test_utils.py | model/model_training/tests/test_utils.py | from argparse import Namespace
import pytest
from model_training.utils.utils import TOKENIZER_CONFIGS, get_tokenizer, match_tokenizer_name
def test_tokenizer():
get_tokenizer(Namespace(model_name="Salesforce/codegen-2B-multi", cache_dir=".cache"))
get_tokenizer(Namespace(model_name="facebook/galactica-1.3b",... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tests/test_patched_falcon.py | model/model_training/tests/test_patched_falcon.py | import torch
from model_training.models.patching import patch_model
from transformers import AutoTokenizer
from transformers.models.falcon.modeling_falcon import FalconForCausalLM
def test_flash_attention_falcon_patch(device="cuda:0"):
model_name = "tiiuae/falcon-7b"
dtype = torch.bfloat16
tokenizer = Au... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tests/test_ranking_collator.py | model/model_training/tests/test_ranking_collator.py | from argparse import Namespace
import pytest
import torch
from model_training.custom_datasets import get_one_dataset
from model_training.custom_datasets.formatting import (
QA_SPECIAL_TOKENS,
DatasetEntryRm,
Role,
Utterance,
create_dataset_entry_qa,
)
from model_training.custom_datasets.ranking_col... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tests/test_formatting.py | model/model_training/tests/test_formatting.py | import pytest
from model_training.custom_datasets.formatting import QA_SPECIAL_TOKENS, DatasetEntrySft, Role, Utterance
def test_dataset_entry_formatting_missing_lang():
ds_entry = DatasetEntrySft(
conversation=[
Utterance(
text="What is the capital of France?",
... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tests/__init__.py | model/model_training/tests/__init__.py | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false | |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tests/test_rm_loading.py | model/model_training/tests/test_rm_loading.py | from argparse import Namespace
import model_training.models.reward_model # noqa: F401
from model_training.models.reward_model import GPTNeoXRewardModel
from model_training.utils.utils import get_tokenizer
from transformers import AutoModelForSequenceClassification, AutoTokenizer
def test_convert_model(
model_na... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tests/test_dialogue_data_collator.py | model/model_training/tests/test_dialogue_data_collator.py | import pytest
import torch
from model_training.custom_datasets.dialogue_collator import DialogueDataCollator
from model_training.custom_datasets.formatting import QA_SPECIAL_TOKENS, create_dataset_entry_qa
from model_training.utils.utils import match_tokenizer_name
from transformers.models.auto.tokenization_auto import... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/tests/test_patched_llama.py | model/model_training/tests/test_patched_llama.py | import torch
from model_training.models.patching import patch_model
from transformers import AutoModelForCausalLM, AutoTokenizer
def test_flash_attention_patch(dtype=torch.float16, device="cuda:0", llama_path="/mnt/data/llama2/Llama-2-7b"):
tokenizer = AutoTokenizer.from_pretrained(llama_path)
tokenizer.add_s... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/models/prefix_llama.py | model/model_training/models/prefix_llama.py | # Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved.
#
# This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX
# and OPT implementations in this library. It has been modified from its
# original forms to accommodate minor architectural differences compared
# to GPT-NeoX and OPT... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | true |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/models/peft_modeling.py | model/model_training/models/peft_modeling.py | from dataclasses import dataclass
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from model_training.utils.utils import get_all_linear_layers, get_model, get_tokenizer, merge_dicts
from peft import LoraConfig, PeftModel, PrefixTuningConfig, get_peft_model, prepare_model_for_int8_trai... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/models/patching_neox.py | model/model_training/models/patching_neox.py | import torch
import torch.nn as nn
import transformers
from .patching_utils import compute_flash_attention
def neox_forward_with_flash_attn(
self: transformers.models.gpt_neox.modeling_gpt_neox.GPTNeoXAttention,
flash_attn: nn.Module, # flash_attn.modules.mha.FlashSelfAttention
query: torch.Tensor,
... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/models/gptj.py | model/model_training/models/gptj.py | # Taken from https://github.com/sleekmike/Finetune_GPT-J_6B_8-bit/blob/master/gpt-j-6b-8-bit.py
import torch
import torch.nn.functional as F
import transformers
from bitsandbytes.functional import dequantize_blockwise, quantize_blockwise
from torch import nn
from torch.cuda.amp import custom_bwd, custom_fwd
from trans... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/models/reward_model.py | model/model_training/models/reward_model.py | from dataclasses import dataclass
from typing import Literal, Optional
import torch
import torch.nn as nn
from transformers import AutoConfig, AutoModelForSequenceClassification
from transformers.models.gpt_neox.modeling_gpt_neox import GPTNeoXConfig, GPTNeoXModel, GPTNeoXPreTrainedModel
from transformers.utils import... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/models/patching.py | model/model_training/models/patching.py | from __future__ import annotations # To make it not choke over FlashSelfAttention
import warnings
from functools import partial
from typing import Callable, Optional
import torch.nn as nn
import transformers
from transformers import (
AutoConfig,
FalconForCausalLM,
FalconModel,
GPTNeoXForCausalLM,
... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/models/patching_falcon.py | model/model_training/models/patching_falcon.py | from typing import Optional, Tuple
import torch
import torch.nn as nn
from .patching_utils import compute_flash_attention
def falcon_forward_with_flash_attn(
self,
flash_attn: nn.Module, # flash_attn.modules.mha.FlashSelfAttention
hidden_states: torch.Tensor,
alibi: Optional[torch.Tensor],
atte... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/models/patching_llama.py | model/model_training/models/patching_llama.py | import math
import warnings
from typing import Optional, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from transformers.models.llama.modeling_llama import LlamaAttention, apply_rotary_pos_emb, repeat_kv
from .patching_utils import compute_flash_attention
# adapted from https://github.com... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/models/__init__.py | model/model_training/models/__init__.py | import transformers
def freeze_top_n_layers(model, target_layers):
# its possible we can simply detect which module is a ModuleList
# and simply freeze the module without doing string parsing
for name, param in model.named_parameters():
if "embed" in name:
param.requires_grad = False
... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/models/patching_utils.py | model/model_training/models/patching_utils.py | import torch
import torch.nn.functional as F
def compute_flash_attention(flash_attn, q, k, v, attention_mask=None, head_mask=None):
# q, k, v: [bs, seq_len, num_attention_heads, attn_head_size]
# attention_mask (float): [bs, seq_len]
batch_size, max_len = q.size(0), q.size(1)
qkv = torch.stack([q, k,... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/models/rope.py | model/model_training/models/rope.py | import torch
# rotary pos emb helpers (torch.jit.script does not seem to support staticmethod...)
def rotate_half(x):
x1, x2 = x[..., : x.shape[-1] // 2], x[..., x.shape[-1] // 2 :]
return torch.cat((-x2, x1), dim=-1)
class RWNTKScaledRope(torch.nn.Module):
"""
NTK-Scaled RoPE for RefinedWebModel
... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/utils/utils_rl.py | model/model_training/utils/utils_rl.py | import tritonclient.grpc as client_util
from tritonclient.utils import np_to_triton_dtype
def prepare_tensor(name: str, input):
t = client_util.InferInput(name, input.shape, np_to_triton_dtype(input.dtype))
t.set_data_from_numpy(input)
return t
| python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/utils/utils.py | model/model_training/utils/utils.py | import argparse
import copy
import math
import random
from distutils.util import strtobool
from pathlib import Path
from typing import List, NamedTuple
import evaluate
import torch
import transformers
import yaml
from model_training.custom_datasets import get_one_dataset
from model_training.custom_datasets.formatting ... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/utils/losses.py | model/model_training/utils/losses.py | import torch
import torch.nn.functional as F
from torch import nn
class CrossEntropyLoss(nn.CrossEntropyLoss):
def __init__(self, weight=None, size_average=None, ignore_index=-100, reduce=None, reduction="mean"):
super().__init__(weight, size_average, ignore_index, reduce, "none")
self._reduction ... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_training/utils/ppo_utils.py | model/model_training/utils/ppo_utils.py | import json
import math
import os
import warnings
from time import time
from typing import List, Tuple
import numpy as np
import torch
# import torch.distributed as dist
import tritonclient.grpc as client_util
import trlx.utils.logging as logging
from huggingface_hub import hf_hub_download
# from torch import nn
fro... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_eval/eval_datasets.py | model/model_eval/eval_datasets.py | from collections import defaultdict
import torch
from model_training.custom_datasets.ranking_collator import RankingDataCollator
from torch.utils.data import DataLoader, Dataset
def get_sampling_dataloader(data, tokenizer, max_length, batch_size):
collate_fn = SamplingDataCollator(tokenizer, max_length=max_lengt... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_eval/sampling_score.py | model/model_eval/sampling_score.py | import argparse
import json
import model_training.models.reward_model # noqa: F401 (registers reward model for AutoModel loading)
import numpy as np
import pandas as pd
import torch
from eval_datasets import get_sampling_dataloader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from utils ... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_eval/eval_rm.py | model/model_eval/eval_rm.py | import argparse
from collections import defaultdict
import numpy as np
import torch
from model_training.custom_datasets.rank_datasets import HellaSwagDataset, HFDataset, SHPDataset
from model_training.custom_datasets.ranking_collator import RankingDataCollator
from model_training.metrics import RewardMetrics
from torc... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_eval/utils.py | model/model_eval/utils.py | import json
import os
import numpy as np
def load_sampling_data(path):
"""
Load sampling data and ensure appropriate keys are present.
"""
if os.path.exists(path):
data = json.load(open(path))
else:
raise FileNotFoundError(f"Sampling data {path} not found")
if "prompts" not ... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_eval/rejection_sampling.py | model/model_eval/rejection_sampling.py | import argparse
import model_training.models.reward_model # noqa: F401 (registers reward model for AutoModel loading)
import numpy as np
import torch
from eval_datasets import RejectionSamplingDataset, SamplingDataCollator
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassifica... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_eval/__init__.py | model/model_eval/__init__.py | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false | |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_eval/manual/subsample_dataset.py | model/model_eval/manual/subsample_dataset.py | import argparse
import gzip
import json
import random
from pathlib import Path
from typing import Optional
import pydantic
from oasst_data import ExportMessageTree
def load_message_trees(
input_file_path: str | Path,
lang_codes: list[str],
tree_state: str,
max_length: Optional[int] = None,
) -> list[... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
LAION-AI/Open-Assistant | https://github.com/LAION-AI/Open-Assistant/blob/f1e6ed9526f5817531f3ab85441a40b3671ddccb/model/model_eval/manual/sampling_report.py | model/model_eval/manual/sampling_report.py | import argparse
import gzip
import json
import random
import re
from collections import OrderedDict
from datetime import datetime
from pathlib import Path
from typing import Any, Optional
import pydantic
import torch
from model_training.models.peft_modeling import load_peft_model
from tqdm import tqdm
from transformer... | python | Apache-2.0 | f1e6ed9526f5817531f3ab85441a40b3671ddccb | 2026-01-04T14:41:20.303953Z | false |
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