repo_id stringlengths 15 86 | file_path stringlengths 28 180 | content stringlengths 1 1.75M | __index_level_0__ int64 0 0 |
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hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/finetune_rag_ray_end2end.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}"
#creates the custom knowlegebase
python use_own_knowledge_dataset.py \
--csv_path /DIR/SQUAD-KB/squad-kb.csv \
--output_dir /DIR/SQUA... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/kb_encode_utils.py | import os
from functools import partial
from glob import glob
import faiss
from datasets import Features, Sequence, Value, concatenate_datasets, load_dataset, load_from_disk
from transformers import DPRContextEncoder, DPRContextEncoderTokenizerFast
def split_text(text, n=100, character=" "):
"""Split the text e... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/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 |
hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever | hf_public_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 |
hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever | hf_public_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 |
hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | hf_public_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 |
hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | hf_public_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 |
hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | hf_public_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 |
hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | hf_public_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 |
hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | hf_public_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 |
hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | hf_public_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 |
hf_public_repos/transformers/examples/research_projects/rag-end2end-retriever/test_run | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/performer/README.md | # Performer fine-tuning
Example authors: @TevenLeScao, @Patrickvonplaten
Paper authors: Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy Colwell, Adrian Weller
## Requirements
`datase... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/performer/modeling_flax_performer_utils.py | # coding=utf-8
# Copyright 2020 The Google Research Authors.
#
# 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 applicab... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/performer/full_script.sh | TOKENIZERS_PARALLELISM=true python run_mlm_performer.py --output_dir experiments --dataset_name wikipedia --dataset_config_name 20200501.en --model_name_or_path bert-large-cased --tokenizer_name bert-large-cased --do_train --overwrite_output_dir --per_device_train_batch_size 4 --learning_rate 5e-4 --warmup_steps 100 -... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/performer/run_mlm_performer.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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/performer/sanity_script.sh | TOKENIZERS_PARALLELISM=true python run_mlm_performer.py --output_dir experiments --dataset_name wikipedia --dataset_config_name 20200501.simple --model_name_or_path bert-base-cased --tokenizer_name bert-base-cased --do_train --overwrite_output_dir --per_device_train_batch_size 4 --learning_rate 5e-4 --warmup_steps 100... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/performer/modeling_flax_performer.py | # coding=utf-8
# Copyright 2018 The Google Flax Team Authors 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
... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects/information-gain-filtration | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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" \
--evaluation_strategy="steps" \
--save_steps="500" \
--eval_steps="100" \
--logging_steps="50" \
--learning_rate="5e-4" \
--warmup_steps="... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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" \
--evaluation_strategy="steps" \
--save_total_limit="3" \
--save_steps="500" \
--eval_steps="100" \
--logging_steps="50" \
--learning_rate... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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" \
--evaluation_strategy="steps" \
--save_steps="500" \
--eval_steps="100" \
--logging_... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_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" \
--evaluation_strateg... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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" \
--evaluation_strategy="steps" \
--save_steps="500" \
--eval_steps="100" \
--logging_steps="50" \
-... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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" \
--evaluation_strategy="steps" \
--save_total_limit="3" \
--save_steps="500" \
--eval_steps="100" \
--logging_steps="50" \
--learning_rate="5e-4... | 0 |
hf_public_repos/transformers/examples/research_projects/wav2vec2 | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/decision_transformer/requirements.txt | absl-py==1.0.0
aiohttp==3.8.5
aiosignal==1.2.0
alembic==1.7.7
appdirs==1.4.4
APScheduler==3.9.1
arrow==1.2.2
asttokens==2.0.5
astunparse==1.6.3
async-timeout==4.0.2
attrs==21.4.0
audioread==2.1.9
autopage==0.5.0
backcall==0.2.0
backoff==1.11.1
backports.zoneinfo==0.2.1
binaryornot==0.4.4
black==22.1.0
boto3==1.16.34
bo... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/decision_transformer/run_decision_transformer.py | import gym
import numpy as np
import torch
from mujoco_py import GlfwContext
from transformers import DecisionTransformerModel
GlfwContext(offscreen=True) # Create a window to init GLFW.
def get_action(model, states, actions, rewards, returns_to_go, timesteps):
# we don't care about the past rewards in this m... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/layoutlmv3/requirements.txt | datasets
seqeval
pillow
| 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/layoutlmv3/README.md | <!---
Copyright 2022 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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/layoutlmv3/run_funsd_cord.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2022 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-... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/mlm_wwm/requirements.txt | datasets >= 1.1.3
sentencepiece != 0.1.92
protobuf
ltp
| 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/jax-projects/README.md | # Flax/JAX community week 🤗
Welcome to the Flax/JAX community week! The goal of this week is to make compute-intensive NLP and CV projects (like pre-training BERT, GPT2, CLIP, ViT)
practicable for a wider audience of engineers and researchers.
To do so, we will try to teach **you** how to effectively use JAX/Flax o... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/jax-projects/HOW_TO_PROPOSE_PROJECT.md | # How to propose a Flax/JAX + Transformers project
Great that you've opened this document!
While we at 🤗 are proposing a couple of projects, we strongly
believe that the community can come up with much more **creative**, **fun**, and
**impactful** projects on their own. This being said, we are really looking forw... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/big_bird/requirements.txt | git+https://github.com/huggingface/transformers@main
datasets
sentencepiece
wandb
flax
jsonlines
| 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/big_bird/README.md |
Author: [@vasudevgupta7](https://github.com/thevasudevgupta/)
## Intro
In this project, we fine-tuned [**BigBird**](https://arxiv.org/abs/2007.14062) on [**natural-questions**](https://huggingface.co/datasets/natural_questions) dataset for **question-answering** task on long documents. **BigBird**, is a **sparse-att... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/big_bird/prepare_natural_questions.py | import os
import jsonlines
import numpy as np
from tqdm import tqdm
DOC_STRIDE = 2048
MAX_LENGTH = 4096
SEED = 42
PROCESS_TRAIN = os.environ.pop("PROCESS_TRAIN", "false")
CATEGORY_MAPPING = {"null": 0, "short": 1, "long": 2, "yes": 3, "no": 4}
def _get_single_answer(example):
def choose_first(answer, is_long_a... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/big_bird/bigbird_flax.py | import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization import from_bytes, to_bytes
from... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/big_bird/sweep_flax.yaml | command:
- python3
- train.py
method: random
parameters:
lr:
values: [4e-5, 3e-5]
warmup_steps:
values: [20000, 15000, 10000, 5000]
weight_decay:
distribution: normal
mu: 1e-2
sigma: 2e-3
metric:
... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/big_bird/evaluate.py | import jax
import jax.numpy as jnp
from bigbird_flax import FlaxBigBirdForNaturalQuestions
from datasets import load_from_disk
from transformers import BigBirdTokenizerFast
CATEGORY_MAPPING = {0: "null", 1: "short", 2: "long", 3: "yes", 4: "no"}
PUNCTUATION_SET_TO_EXCLUDE = set("".join(["‘", "’", "´", "`", ".", ",",... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/big_bird/train.py | import os
from dataclasses import replace
import jax
import wandb
from bigbird_flax import Args, DataCollator, FlaxBigBirdForNaturalQuestions, Trainer, build_tx, train_step, val_step
from datasets import load_dataset
from flax import jax_utils
from transformers import BigBirdTokenizerFast
if __name__ == "__main__":... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/dataset-streaming/README.md | <!---
Copyright 2021 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 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/dataset-streaming/run_mlm_flax_stream.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2021 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-... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/hybrid_clip/requirements.txt | jax>=0.2.8
jaxlib>=0.1.59
flax>=0.3.5
optax>=0.0.8
-f https://download.pytorch.org/whl/torch_stable.html
torch==1.9.0+cpu
-f https://download.pytorch.org/whl/torch_stable.html
torchvision==0.10.0+cpu | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/hybrid_clip/configuration_hybrid_clip.py | import copy
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import logging
logger = logging.get_logger(__name__)
class HybridCLIPConfig(PretrainedConfig):
r"""
:class:`HybridCLIPConfig` is the configuration class to store the configuration of a
:class:`~HybridCLIPM... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/hybrid_clip/README.md | <!---
Copyright 2021 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 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/hybrid_clip/modeling_hybrid_clip.py | # coding=utf-8
# Copyright 2021 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 requir... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/hybrid_clip/run_hybrid_clip.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2021 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-... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/model_parallel/run_clm_mp.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2021 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-... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/model_parallel/README.md | <!---
Copyright 2021 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 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/model_parallel/partitions.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2021 The Google Research Authors and 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://... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/wav2vec2/README.md | # Wav2Vec2 Contrastive Loss PreTraining examples
The following example showcases how to pretrain a wav2vec2 model using the JAX/Flax backend.
Pretraining Wav2Vec2 is rather complex, so it is highly recommended to read the
[official paper](https://arxiv.org/abs/2006.11477).
JAX/Flax allows you to trace pure functions... | 0 |
hf_public_repos/transformers/examples/research_projects/jax-projects | hf_public_repos/transformers/examples/research_projects/jax-projects/wav2vec2/run_wav2vec2_pretrain_flax.py | #!/usr/bin/env python3
import logging
import sys
import time
from dataclasses import field
from pathlib import Path
from typing import Dict, List, Optional, Union
import flax
import jax
import jax.numpy as jnp
import librosa
import numpy as np
import optax
from datasets import DatasetDict, load_dataset
from flax impor... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/fsner/requirements.txt | transformers>=4.9.2 | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/fsner/README.md | <p align="center"> <img src="http://sayef.tech:8082/uploads/FSNER-LOGO-2.png" alt="FSNER LOGO"> </p>
<p align="center">
Implemented by <a href="https://huggingface.co/sayef"> sayef </a>.
</p>
## Overview
The FSNER model was proposed in [Example-Based Named Entity Recognition](https://arxiv.org/abs/2008.10570) by ... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/fsner/setup.py | import setuptools
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
setuptools.setup(
name="fsner",
version="0.0.1",
author="msi sayef",
author_email="msi.sayef@gmail.com",
description="Few-shot Named Entity Recognition",
long_description=long_description,
... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/fsner/pyproject.toml | [build-system]
requires = [
"setuptools>=57.4.0",
"wheel>=0.37.0",
"transformers>=4.9.2"
]
build-backend = "setuptools.build_meta" | 0 |
hf_public_repos/transformers/examples/research_projects/fsner/src | hf_public_repos/transformers/examples/research_projects/fsner/src/fsner/__init__.py | from .model import FSNERModel
from .tokenizer_utils import FSNERTokenizerUtils
__all__ = ["FSNERModel", "FSNERTokenizerUtils"]
| 0 |
hf_public_repos/transformers/examples/research_projects/fsner/src | hf_public_repos/transformers/examples/research_projects/fsner/src/fsner/tokenizer_utils.py | import torch
from transformers import AutoTokenizer
class FSNERTokenizerUtils(object):
def __init__(self, pretrained_model_name_or_path):
self.tokenizer = AutoTokenizer.from_pretrained(pretrained_model_name_or_path)
def tokenize(self, x):
"""
Wrapper function for tokenizing query and... | 0 |
hf_public_repos/transformers/examples/research_projects/fsner/src | hf_public_repos/transformers/examples/research_projects/fsner/src/fsner/model.py | import torch
from transformers import AutoModel
class FSNERModel(torch.nn.Module):
"""
The FSNER model implements a few-shot named entity recognition method from the paper `Example-Based Named Entity Recognition <https://arxiv.org/abs/2008.10570>`__ by
Morteza Ziyadi, Yuting Sun, Abhishek Goswami, Jade H... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/xtreme-s/requirements.txt | datasets >= 1.18.0
torch >= 1.5
torchaudio
librosa
jiwer
| 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/xtreme-s/README.md | <!---
Copyright 2022 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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/xtreme-s/run_xtreme_s.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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/mm-imdb/README.md | ## MM-IMDb
Based on the script [`run_mmimdb.py`](https://github.com/huggingface/transformers/blob/main/examples/research_projects/mm-imdb/run_mmimdb.py).
[MM-IMDb](http://lisi1.unal.edu.co/mmimdb/) is a Multimodal dataset with around 26,000 movies including images, plots and other metadata.
### Training on MM-IMDb
... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/mm-imdb/run_mmimdb.py | # coding=utf-8
# Copyright (c) Facebook, Inc. and its affiliates.
# Copyright (c) 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... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/mm-imdb/utils_mmimdb.py | # coding=utf-8
# Copyright (c) Facebook, Inc. and its affiliates.
# Copyright (c) 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... | 0 |
hf_public_repos/transformers/examples | hf_public_repos/transformers/examples/legacy/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 |
hf_public_repos/transformers/examples | hf_public_repos/transformers/examples/legacy/run_chinese_ref.py | #!/usr/bin/env python
import argparse
import json
from typing import List
from ltp import LTP
from transformers 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:
# https... | 0 |
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