repo_id stringclasses 55
values | file_path stringlengths 42 186 | content stringlengths 1 333k | __index_level_0__ int64 0 0 |
|---|---|---|---|
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/finetune_rag.py | """Finetuning script for RAG models. Adapted from examples.seq2seq.finetune.py"""
import argparse
import copy
import json
import logging
import multiprocessing
import os
import random
import shutil
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Any, Dict, List, T... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/README.md | # End-to-End finetuning of RAG (including DPR retriever) for Question Answering.
This finetuning script is actively maintained by [Shamane Siri](https://github.com/shamanez). Feel free to ask questions on the [Forum](https://discuss.huggingface.co/) or post an issue on [GitHub](https://github.com/huggingface/transform... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/use_own_knowledge_dataset.py | import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import DPRContextE... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/distributed_ray_retriever.py | import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
logger = logging.getLogger(__name__)
class RayRetriever:
def __init__(self):
self.initialized = False
def create_rag_retriever(sel... | 0 |
mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run/test_finetune.sh | # Add parent directory to python path to access lightning_base.py
export PYTHONPATH="../":"${PYTHONPATH}"
#creates the custom knowlegebase
python use_own_knowledge_dataset.py
# Start a single-node Ray cluster.
ray start --head
# A sample finetuning run, you need to specify data_dir, output_dir and model_name_or_pat... | 0 |
mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run/test_rag_new_features.sh | export PYTHONPATH="../":"${PYTHONPATH}"
python use_own_knowledge_dataset.py
ray start --head
python finetune_rag.py \
--model_name_or_path facebook/rag-token-base \
--model_type rag_token \
--context_encoder_name facebook/dpr-ctx_encoder-multiset-base \
--fp16 \
--gpus 1 \
--profile \
--e... | 0 |
mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run/dummy-train-data/val.source | What does Moses' rod turn into ?
Who is Aron?
Where did Moses grow up ?
What happens at the command of the Moses ?
Who manages the Pokémon ?
Who owned the Pokémon trademark ?
What else include in Pokémon franchise ?
How many seasons in Pokémon animme series ? | 0 |
mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run/dummy-train-data/train.source | What does Moses' rod turn into ?
Who is Aron?
Where did Moses grow up ?
What happens at the command of the Moses ?
Who manages the Pokémon ?
Who owned the Pokémon trademark ?
What else include in Pokémon franchise ?
How many seasons in Pokémon animme series ?
What does Moses' rod turn into ?
Who is Aron?
Where did Mose... | 0 |
mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run/dummy-train-data/train.target | to a snake
Moses' assistant
Egyptian royal court
let his rod turn in to a snake
The Pokémon Company
Nintendo
world's top-selling toy brand, the top-selling trading card game
over 20 seasons
to a snake
Moses' assistant
Egyptian royal court
let his rod turn in to a snake
The Pokémon Company
Nintendo
world's top-selling... | 0 |
mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run/dummy-train-data/test.source | What does Moses' rod turn into ?
Who is Aron?
Where did Moses grow up ?
What happens at the command of the Moses ?
Who manages the Pokémon ?
Who owned the Pokémon trademark ?
What else include in Pokémon franchise ?
How many seasons in Pokémon animme series ?
| 0 |
mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run/dummy-train-data/val.target | to a snake
Moses' assistant
Egyptian royal court
let his rod turn in to a snake
The Pokémon Company
Nintendo
world's top-selling toy brand, the top-selling trading card game
over 20 seasons | 0 |
mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run/dummy-train-data/test.target | to a snake
Moses' assistant
Egyptian royal court
let his rod turn in to a snake
The Pokémon Company
Nintendo
world's top-selling toy brand, the top-selling trading card game
over 20 seasons
| 0 |
mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | mavonic_private_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run/dummy-kb/my_knowledge_dataset.csv | Aaron Aaron Aaron ( or ; "Ahärôn") is a prophet, high priest, and the brother of Moses in the Abrahamic religions. Knowledge of Aaron, along with his brother Moses, comes exclusively from religious texts, such as the Bible and Quran. The Hebrew Bible relates that, unlike Moses, who grew up in the Egyptian royal court, ... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/bertology/run_prune_gpt.py | #!/usr/bin/env python3
""" This script is adapted from the Bertology pruning code (https://github.com/huggingface/transformers/blob/783d7d2629e97c5f0c5f9ef01b8c66410275c204/examples/research_projects/bertology/run_bertology.py)
to prune GPT-like models. The author is @altsoph.
"""
import argparse
import logging
import... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/bertology/requirements.txt | transformers == 3.5.1
| 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/bertology/run_bertology.py | #!/usr/bin/env python3
# Copyright 2018 CMU and The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/lxmert/requirements.txt | appdirs==1.4.3
argon2-cffi==20.1.0
async-generator==1.10
attrs==20.2.0
backcall==0.2.0
CacheControl==0.12.6
certifi==2023.7.22
cffi==1.14.2
chardet==3.0.4
click==7.1.2
colorama==0.4.3
contextlib2==0.6.0
cycler==0.10.0
datasets==1.0.0
decorator==4.4.2
defusedxml==0.6.0
dill==0.3.2
distlib==0.3.0
distro==1.4.0
entrypoint... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/lxmert/utils.py | """
coding=utf-8
Copyright 2018, Antonio Mendoza Hao Tan, Mohit Bansal, Huggingface team :)
Adapted From Facebook Inc, Detectron2
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://w... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/lxmert/visualizing_image.py | """
coding=utf-8
Copyright 2018, Antonio Mendoza Hao Tan, Mohit Bansal
Adapted From Facebook Inc, Detectron2
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/license... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/lxmert/extracting_data.py | import getopt
import json
import os
# import numpy as np
import sys
from collections import OrderedDict
import datasets
import numpy as np
import torch
from modeling_frcnn import GeneralizedRCNN
from processing_image import Preprocess
from utils import Config
"""
USAGE:
``python extracting_data.py -i <img_dir> -o ... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/lxmert/demo.ipynb | # %pip install-r requirements.txtfrom IPython.display import clear_output, Image, display
import PIL.Image
import io
import json
import torch
import numpy as np
from processing_image import Preprocess
from visualizing_image import SingleImageViz
from modeling_frcnn import GeneralizedRCNN
from utils import Config
import... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/lxmert/processing_image.py | """
coding=utf-8
Copyright 2018, Antonio Mendoza Hao Tan, Mohit Bansal
Adapted From Facebook Inc, Detectron2
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/license... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/lxmert/README.md | # LXMERT DEMO
1. make a virtualenv: ``virtualenv venv`` and activate ``source venv/bin/activate``
2. install reqs: ``pip install -r ./requirements.txt``
3. usage is as shown in demo.ipynb
| 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/lxmert/modeling_frcnn.py | """
coding=utf-8
Copyright 2018, Antonio Mendoza Hao Tan, Mohit Bansal
Adapted From Facebook Inc, Detectron2 && Huggingface Co.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/information-gain-filtration/requirements.txt | matplotlib
numpy>=1.17.2
joblib>=0.13.2
scipy
torch>=1.10.1
transformers>=3.5 | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/information-gain-filtration/run_clm_igf.py | # Copyright 2022 - Intel Corp. All rights reserved.
# Authors: Mayank Kumar Raunak, Javier Turek, Nicole Beckage
"""
Implementation of a new method for fine-tuning transformer models that we call
Information Gain Filtration 'IGF' on WikiText data set and compared the results
with the standard fine-tuning method
Steps... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/information-gain-filtration/README.md |
# Information Gain Filtration(IGF)
Authors @Tuko @mraunak
This folder contains the code how to implement IGF for finetuning on GPT-2.
## What is IGF?
Here we present a general fine-tuning method that we call information gain filtration for improving the overall training efficiency and final
performance of language... | 0 |
mavonic_private_repos/transformers/examples/research_projects/information-gain-filtration | mavonic_private_repos/transformers/examples/research_projects/information-gain-filtration/igf/igf.py | # Copyright 2022 - Intel Corp. All rights reserved.
# Authors: Mayank Kumar Raunak, Javier Turek, Nicole Backage
import copy
import logging
import random
import joblib
import numpy as np
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AdamW, G... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/distillation/grouped_batch_sampler.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team and Facebook, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/distillation/requirements.txt | transformers
gitpython==3.1.41
tensorboard>=1.14.0
tensorboardX==1.8
psutil==5.6.6
scipy>=1.4.1
| 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/distillation/utils.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team and Facebook, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/distillation/train.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/distillation/run_squad_w_distillation.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a cop... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/distillation/distiller.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team and Facebook, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/distillation/lm_seqs_dataset.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team and Facebook, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/distillation/README.md | # Distil*
Author: @VictorSanh
This folder contains the original code used to train Distil* as well as examples showcasing how to use DistilBERT, DistilRoBERTa and DistilGPT2.
**January 20, 2020 - Bug fixing** We have recently discovered and fixed [a bug](https://github.com/huggingface/transformers/commit/48cbf267c98... | 0 |
mavonic_private_repos/transformers/examples/research_projects/distillation | mavonic_private_repos/transformers/examples/research_projects/distillation/scripts/token_counts.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 0 |
mavonic_private_repos/transformers/examples/research_projects/distillation | mavonic_private_repos/transformers/examples/research_projects/distillation/scripts/extract_distilbert.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 0 |
mavonic_private_repos/transformers/examples/research_projects/distillation | mavonic_private_repos/transformers/examples/research_projects/distillation/scripts/binarized_data.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 0 |
mavonic_private_repos/transformers/examples/research_projects/distillation | mavonic_private_repos/transformers/examples/research_projects/distillation/scripts/extract.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 0 |
mavonic_private_repos/transformers/examples/research_projects/distillation | mavonic_private_repos/transformers/examples/research_projects/distillation/training_configs/distilgpt2.json | {
"initializer_range": 0.02,
"layer_norm_epsilon": 0.00001,
"n_embd": 768,
"n_head": 12,
"n_layer": 6,
"n_positions": 1024,
"vocab_size": 50257
} | 0 |
mavonic_private_repos/transformers/examples/research_projects/distillation | mavonic_private_repos/transformers/examples/research_projects/distillation/training_configs/distilroberta-base.json | {
"vocab_size": 50265,
"hidden_size": 768,
"num_hidden_layers": 6,
"num_attention_heads": 12,
"intermediate_size": 3072,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"attention_probs_dropout_prob": 0.1,
"max_position_embeddings": 514,
"type_vocab_size": 1,
"initializer_r... | 0 |
mavonic_private_repos/transformers/examples/research_projects/distillation | mavonic_private_repos/transformers/examples/research_projects/distillation/training_configs/distilbert-base-uncased.json | {
"activation": "gelu",
"attention_dropout": 0.1,
"dim": 768,
"dropout": 0.1,
"hidden_dim": 3072,
"initializer_range": 0.02,
"max_position_embeddings": 512,
"n_heads": 12,
"n_layers": 6,
"sinusoidal_pos_embds": true,
"tie_weights_": true,
"vocab_size": 30522
}
| 0 |
mavonic_private_repos/transformers/examples/research_projects/distillation | mavonic_private_repos/transformers/examples/research_projects/distillation/training_configs/distilbert-base-multilingual-cased.json | {
"activation": "gelu",
"attention_dropout": 0.1,
"dim": 768,
"dropout": 0.1,
"hidden_dim": 3072,
"initializer_range": 0.02,
"max_position_embeddings": 512,
"n_heads": 12,
"n_layers": 6,
"sinusoidal_pos_embds": true,
"tie_weights_": true,
"vocab_size": 119547
}
| 0 |
mavonic_private_repos/transformers/examples/research_projects/distillation | mavonic_private_repos/transformers/examples/research_projects/distillation/training_configs/distilbert-base-cased.json | {
"activation": "gelu",
"attention_dropout": 0.1,
"dim": 768,
"dropout": 0.1,
"hidden_dim": 3072,
"initializer_range": 0.02,
"max_position_embeddings": 512,
"n_heads": 12,
"n_layers": 6,
"sinusoidal_pos_embds": true,
"tie_weights_": true,
"vocab_size": 28996
}
| 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/zero-shot-distillation/distill_classifier.py | import logging
import os
import sys
from dataclasses import dataclass, field
from typing import List, Optional
import torch
from datasets import Dataset
from torch import nn
from tqdm.auto import tqdm
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
HfArgumentParser,
Train... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/zero-shot-distillation/README.md | # Zero-shot classifier distillation
Author: @joeddav
This script provides a way to improve the speed and memory performance of a zero-shot classifier by training a more
efficient student model from the zero-shot teacher's predictions over an unlabeled dataset.
The zero-shot classification pipeline uses a model pre-... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/robust-speech-event/eval.py | #!/usr/bin/env python3
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def log_results(result: Dataset, args: Dict[str, str]):
"""DO NOT CHANGE. This function computes and logs t... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/robust-speech-event/run_speech_recognition_ctc_bnb.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/robust-speech-event/run_speech_recognition_ctc_streaming.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/robust-speech-event/README.md | # Robust Speech Challenge 🤗
Welcome to the robust speech recognition challenge 🎙️ !
The goal of this event is to build **robust**, **real-world** speech recognition (ASR) systems in as many languages as possible 🌏🌍🌎.
If necessary and available, free access to a V100S 32 GB GPU will kindly be provided by the [OVH... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/longform-qa/eli5_utils.py | import functools
import math
import os # noqa: F401
from random import choice, randint
from time import time
import datasets # noqa: F401
import faiss # noqa: F401
import numpy as np
import pandas as pd
import torch
import torch.utils.checkpoint as checkpoint
from elasticsearch import Elasticsearch # noqa: F401
fr... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/longform-qa/requirements.txt | datasets >= 1.1.3
faiss-cpu
streamlit
elasticsearch
| 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/longform-qa/eli5_app.py | import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from eli5_utils import (
embed_questions_for_retrieval,
make_qa_s2s_model,
qa_s2s_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers impor... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/longform-qa/README.md | # Long Form Question Answering
Author: @yjernite
This folder contains the code for the Long Form Question answering [demo](http://35.226.96.115:8080/) as well as methods to train and use a fully end-to-end Long Form Question Answering system using the [🤗transformers](https://github.com/huggingface/transformers) and ... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/mlm_wwm/requirements.txt | datasets >= 1.1.3
sentencepiece != 0.1.92
protobuf
ltp
| 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/mlm_wwm/run_chinese_ref.py | import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def _is_chinese_char(cp):
"""Checks whether CP is the codepoint of a CJK character."""
# This defines a "chinese character" as anything in the CJK Unicode block:
#... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/mlm_wwm/run_mlm_wwm.py | # coding=utf-8
# Copyright 2020 The HuggingFace Team All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/mlm_wwm/README.md | <!---
Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or ... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/distributed_pytorch_retriever.py | import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
logger = logging.getLogger(__name__)
class RagPyTorchDistributedRetriever(RagRetriever):
"""
A distributed retriever built on top of ... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/_test_finetune_rag.py | import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
logging.b... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/lightning_base.py | import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelForQuestionAnswering,
... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/requirements.txt | faiss-cpu >= 1.6.3
datasets >= 1.0.1
psutil >= 5.7.0
torch >= 1.4.0
ray >= 1.10.0
pytorch-lightning >= 1.5.10, <=1.6.0
transformers
GitPython | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/callbacks_rag.py | import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def count_trainable_parameters(model):
model_paramet... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/parse_dpr_relevance_data.py | """
This script reads DPR retriever training data and parses each datapoint. We save a line per datapoint.
Each line consists of the query followed by a tab-separated list of Wikipedia page titles constituting
positive contexts for a given query.
"""
import argparse
import json
from tqdm import tqdm
def main():
... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/finetune_rag.sh | # Add parent directory to python path to access lightning_base.py
export PYTHONPATH="../":"${PYTHONPATH}"
# A sample finetuning run, you need to specify data_dir, output_dir and model_name_or_path
# run ./examples/rag/finetune_rag.sh --help to see all the possible options
python examples/rag/finetune_rag.py \
--d... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/utils_rag.py | import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from transfo... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/eval_rag.py | """ Evaluation script for RAG models."""
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as trans... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/__init__.py | import os
import sys
sys.path.insert(1, os.path.dirname(os.path.realpath(__file__)))
| 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/test_distributed_retriever.py | import json
import os
import shutil
import sys
import tempfile
import unittest
from unittest import TestCase
from unittest.mock import patch
import faiss
import numpy as np
from datasets import Dataset
from transformers import BartConfig, BartTokenizer, DPRConfig, DPRQuestionEncoderTokenizer, RagConfig
from transform... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/finetune_rag_ray.sh | # Sample script to finetune RAG using Ray for distributed retrieval.
# Add parent directory to python path to access lightning_base.py
export PYTHONPATH="../":"${PYTHONPATH}"
# Start a single-node Ray cluster.
ray start --head
# A sample finetuning run, you need to specify data_dir, output_dir and model_name_or_path... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/finetune_rag.py | """Finetuning script for RAG models. Adapted from examples.seq2seq.finetune.py"""
import argparse
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Any, Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
import... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/README.md | # Intro
Authors: @patrickvonplaten and @lhoestq
Aimed at tackling the knowledge-intensive NLP tasks (think tasks a human wouldn't be expected to solve without access to external knowledge sources), RAG models are seq2seq models with access to a retrieval mechanism providing relevant context documents at training and ... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/use_own_knowledge_dataset.py | import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import (
DPRCo... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/consolidate_rag_checkpoint.py | """
A script creating a RAG checkpoint from a generator and a question encoder checkpoints.
"""
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def consolidate(
model_type,
generator_name_or_path: str,
... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/rag/distributed_ray_retriever.py | import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
logger = logging.getLogger(__name__)
class RayRetriever:
def __init__(self):
self.initialized = False
def create_rag_retriever(sel... | 0 |
mavonic_private_repos/transformers/examples/research_projects/rag | mavonic_private_repos/transformers/examples/research_projects/rag/test_data/my_knowledge_dataset.csv | Aaron Aaron Aaron ( or ; "Ahärôn") is a prophet, high priest, and the brother of Moses in the Abrahamic religions. Knowledge of Aaron, along with his brother Moses, comes exclusively from religious texts, such as the Bible and Quran. The Hebrew Bible relates that, unlike Moses, who grew up in the Egyptian royal court, ... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/FINE_TUNE_XLSR_WAV2VEC2.md | # Fine-Tuning week of XLSR-Wav2Vec2 on 60 languages 🌍
Welcome to the fine-tuning week! The goal of this week is to have state-of-the-art automatic speech recognition (ASR) models in as many languages as possible. The fine-tuning week ends on Friday, the 26th March at midnight PST time.
Participants are encouraged to... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/finetune_large_xlsr_53_arabic_speech_corpus.sh | #!/usr/bin/env bash
python run_asr.py \
--output_dir="./wav2vec2-large-xlsr-53-arabic-speech-corpus" \
--num_train_epochs="50" \
--per_device_train_batch_size="1" \
--per_device_eval_batch_size="1" \
--gradient_accumulation_steps="8" \
--eval_strategy="steps" \
--save_steps="500" \
--eval_steps="100" \
--logging_steps=... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/ds_config_wav2vec2_zero3.json | {
"fp16": {
"enabled": "auto",
"loss_scale": 0,
"loss_scale_window": 1000,
"initial_scale_power": 16,
"hysteresis": 2,
"min_loss_scale": 1
},
"optimizer": {
"type": "AdamW",
"params": {
"lr": "auto",
"betas": "auto",
... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/finetune_base_100.sh | #!/usr/bin/env bash
python run_asr.py \
--output_dir="./wav2vec2-base-100h" \
--num_train_epochs="30" \
--per_device_train_batch_size="32" \
--per_device_eval_batch_size="32" \
--eval_strategy="steps" \
--save_total_limit="3" \
--save_steps="500" \
--eval_steps="100" \
--logging_steps="50" \
--learning_rate="5e-4" \
--... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/requirements.txt | transformers
datasets
torch>=1.5.0
torchaudio
jiwer==2.2.0
lang-trans==0.6.0
librosa==0.8.0
| 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/finetune_wav2vec2_xlsr_turkish.sh | #!/usr/bin/env bash
python run_common_voice.py \
--model_name_or_path="facebook/wav2vec2-large-xlsr-53" \
--dataset_config_name="tr" \
--output_dir=./wav2vec2-large-xlsr-turkish-demo \
--overwrite_output_dir \
--num_train_epochs="5" \
--per_device_train_batch_size="16" \
--eval_strategy="ste... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/run_alignment.sh | #!/usr/bin/env bash
python alignment.py \
--model_name="arijitx/wav2vec2-xls-r-300m-bengali" \
--wav_dir="./wavs" \
--text_file="script.txt" \
--input_wavs_sr=48000 \
--output_dir="./out_alignment" \
--cuda
| 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/finetune_base_timit_asr.sh | #!/usr/bin/env bash
python run_asr.py \
--output_dir="./wav2vec2-base-timit-asr" \
--num_train_epochs="30" \
--per_device_train_batch_size="20" \
--per_device_eval_batch_size="20" \
--eval_strategy="steps" \
--save_steps="500" \
--eval_steps="100" \
--logging_steps="50" \
--learning_rate="5e-4" \
--warmup_steps="3000" ... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/run_pretrain.py | #!/usr/bin/env python3
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/run_asr.py | #!/usr/bin/env python3
import logging
import pathlib
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Callable, Dict, List, Optional, Set, Union
import datasets
import librosa
import numpy as np
import torch
from lang_trans import arabic
from packaging import version
from torch imp... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/test_wav2vec2_deepspeed.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/alignment.py | # Parts of the code are adapted from the snippets provided in the TorchAudio Wav2Vec forced alignment tutorial.
# The full tutorial can be found here: https://pytorch.org/audio/stable/tutorials/forced_alignment_tutorial.html
import argparse
import os
from dataclasses import dataclass
import torch
import torchaudio
fr... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/finetune_large_lv60_timit_asr.sh | #!/usr/bin/env bash
python run_asr.py \
--output_dir="./wav2vec2-large-lv60-timit-asr" \
--num_train_epochs="30" \
--per_device_train_batch_size="2" \
--per_device_eval_batch_size="2" \
--gradient_accumulation_steps="4" \
--eval_strategy="steps" \
--save_steps="500" \
--eval_steps="100" \
--logging_steps="50" \
--learn... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/run_common_voice.py | #!/usr/bin/env python3
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transformers
from tr... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/finetune_large_lv60_100.sh | #!/usr/bin/env bash
python run_asr.py \
--output_dir="./wav2vec2-large-lv60-100h" \
--num_train_epochs="30" \
--per_device_train_batch_size="16" \
--per_device_eval_batch_size="16" \
--eval_strategy="steps" \
--save_total_limit="3" \
--save_steps="500" \
--eval_steps="100" \
--logging_steps="50" \
--learning_rate="5e-4... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/README.md | **NOTE**: This example is outdated and is not longer actively maintained. Please
follow the new instructions of fine-tuning Wav2Vec2 [here](https://github.com/huggingface/transformers/blob/main/examples/pytorch/speech-recognition/README.md)
## Fine-tuning Wav2Vec2
The `run_asr.py` script allows one to fine-tune pret... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/ds_config_wav2vec2_zero2.json | {
"fp16": {
"enabled": "auto",
"loss_scale": 0,
"loss_scale_window": 1000,
"initial_scale_power": 16,
"hysteresis": 2,
"min_loss_scale": 1
},
"optimizer": {
"type": "AdamW",
"params": {
"lr": "auto",
"betas": "auto",
... | 0 |
mavonic_private_repos/transformers/examples/research_projects/wav2vec2 | mavonic_private_repos/transformers/examples/research_projects/wav2vec2/vocab/buckwalter.json | {
"<pad>": 0,
"<s>": 1,
"</s>": 2,
"<unk>": 3,
"/": 4,
"'": 5,
"|": 6,
">": 7,
"&": 8,
"<": 9,
"}": 10,
"A": 11,
"b": 12,
"p": 13,
"t": 14,
"v": 15,
"j": 16,
"H": 17,
"x": 18,
"d": 19,
"*": 20,
"r": 21,
"z": 22,
"s": 23,
... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/deebert/entropy_eval.sh | #!/bin/bash
export CUDA_VISIBLE_DEVICES=0
PATH_TO_DATA=/h/xinji/projects/GLUE
MODEL_TYPE=bert # bert or roberta
MODEL_SIZE=base # base or large
DATASET=MRPC # SST-2, MRPC, RTE, QNLI, QQP, or MNLI
MODEL_NAME=${MODEL_TYPE}-${MODEL_SIZE}
if [ $MODEL_TYPE = 'bert' ]
then
MODEL_NAME=${MODEL_NAME}-uncased
fi
ENTROPI... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/deebert/requirements.txt | transformers == 3.5.1
| 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/deebert/test_glue_deebert.py | import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger()
def get_setup_file():
parser = argparse... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/deebert/train_deebert.sh | #!/bin/bash
export CUDA_VISIBLE_DEVICES=0
PATH_TO_DATA=/h/xinji/projects/GLUE
MODEL_TYPE=bert # bert or roberta
MODEL_SIZE=base # base or large
DATASET=MRPC # SST-2, MRPC, RTE, QNLI, QQP, or MNLI
MODEL_NAME=${MODEL_TYPE}-${MODEL_SIZE}
EPOCHS=10
if [ $MODEL_TYPE = 'bert' ]
then
EPOCHS=3
MODEL_NAME=${MODEL_NAME... | 0 |
mavonic_private_repos/transformers/examples/research_projects | mavonic_private_repos/transformers/examples/research_projects/deebert/eval_deebert.sh | #!/bin/bash
export CUDA_VISIBLE_DEVICES=0
PATH_TO_DATA=/h/xinji/projects/GLUE
MODEL_TYPE=bert # bert or roberta
MODEL_SIZE=base # base or large
DATASET=MRPC # SST-2, MRPC, RTE, QNLI, QQP, or MNLI
MODEL_NAME=${MODEL_TYPE}-${MODEL_SIZE}
if [ $MODEL_TYPE = 'bert' ]
then
MODEL_NAME=${MODEL_NAME}-uncased
fi
python... | 0 |
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