repo_id stringlengths 15 89 | file_path stringlengths 27 180 | content stringlengths 1 2.23M | __index_level_0__ int64 0 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/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/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 | 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/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/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/pplm/requirements.txt | tensorboard
scikit-learn
seqeval
psutil
sacrebleu
rouge-score
tensorflow_datasets
pytorch-lightning
matplotlib
git-python==1.0.3
faiss-cpu
streamlit
elasticsearch
nltk
pandas
datasets >= 1.1.3
fire
pytest
conllu
sentencepiece != 0.1.92
protobuf
transformers==3.5.1
| 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/pplm/run_pplm.py | #! /usr/bin/env python3
# coding=utf-8
# Copyright (c) 2019 Uber Technologies, 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
#
# Unless ... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/pplm/README.md | # Plug and Play Language Models: a Simple Approach to Controlled Text Generation
Authors: [Sumanth Dathathri](https://dathath.github.io/), [Andrea Madotto](https://andreamad8.github.io/), Janice Lan, Jane Hung, Eric Frank, [Piero Molino](https://w4nderlu.st/), [Jason Yosinski](http://yosinski.com/), and [Rosanne Liu](... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/pplm/pplm_classification_head.py | from torch import nn
class ClassificationHead(nn.Module):
"""Classification Head for transformer encoders"""
def __init__(self, class_size, embed_size):
super().__init__()
self.class_size = class_size
self.embed_size = embed_size
# self.mlp1 = nn.Linear(embed_size, embed_size... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/pplm/run_pplm_discrim_train.py | #! /usr/bin/env python3
# coding=utf-8
# Copyright (c) 2019 Uber Technologies, 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
#
# Unless ... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/deebert/requirements.txt | transformers == 3.5.1
| 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/deebert/run_glue_deebert.py | from __future__ import absolute_import, division, print_function
import argparse
import glob
import logging
import os
import random
import time
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from torch.utils.data.distribute... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/deebert/README.md | # DeeBERT: Early Exiting for *BERT
This is the code base for the paper [DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference](https://www.aclweb.org/anthology/2020.acl-main.204/), modified from its [original code base](https://github.com/castorini/deebert).
The original code base also has information for do... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects/deebert | hf_public_repos/transformers/examples/research_projects/deebert/src/modeling_highway_roberta.py | from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.roberta... | 0 |
hf_public_repos/transformers/examples/research_projects/deebert | hf_public_repos/transformers/examples/research_projects/deebert/src/modeling_highway_bert.py | import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEmbeddings,
BertLayer,
... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/tapex/requirements.txt | numpy
datasets
pandas
nltk | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/tapex/run_wikitablequestions_with_tapex.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2022 The Microsoft and 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.apac... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/tapex/README.md | <!---
Copyright 2022 The Microsoft Inc. and 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/LICENSE-2.0
Unless re... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/tapex/wikisql_utils.py | # coding=utf-8
# Copyright 2022 The Microsoft, The Google and 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/lic... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/tapex/run_wikisql_with_tapex.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2022 The Microsoft and 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.apac... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/tapex/run_tabfact_with_tapex.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2022 The Microsoft and 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.apac... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/movement-pruning/bertarize.py | # Copyright 2020-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 applicable law o... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/movement-pruning/requirements.txt | torch>=1.4.0
-e git+https://github.com/huggingface/transformers.git@352d5472b0c1dec0f420d606d16747d851b4bda8#egg=transformers
knockknock>=0.1.8.1
h5py>=2.10.0
numpy>=1.18.2
scipy>=1.4.1
| 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/movement-pruning/counts_parameters.py | # Copyright 2020-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 applicable law o... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/movement-pruning/README.md | # Movement Pruning: Adaptive Sparsity by Fine-Tuning
Author: @VictorSanh
*Magnitude pruning is a widely used strategy for reducing model size in pure supervised learning; however, it is less effective in the transfer learning regime that has become standard for state-of-the-art natural language processing application... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/movement-pruning/masked_run_squad.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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/movement-pruning/masked_run_glue.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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/movement-pruning/Saving_PruneBERT.ipynb | # Includes
import h5py
import os
import json
from collections import OrderedDict
from scipy import sparse
import numpy as np
import torch
from torch import nn
from transformers import *
os.chdir("../../")# Load fine-pruned model and quantize the model
model = BertForQuestionAnswering.from_pretrained("huggingface/... | 0 |
hf_public_repos/transformers/examples/research_projects/movement-pruning | hf_public_repos/transformers/examples/research_projects/movement-pruning/emmental/configuration_bert_masked.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 |
hf_public_repos/transformers/examples/research_projects/movement-pruning | hf_public_repos/transformers/examples/research_projects/movement-pruning/emmental/__init__.py | from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 0 |
hf_public_repos/transformers/examples/research_projects/movement-pruning | hf_public_repos/transformers/examples/research_projects/movement-pruning/emmental/modeling_bert_masked.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 |
hf_public_repos/transformers/examples/research_projects/movement-pruning/emmental | hf_public_repos/transformers/examples/research_projects/movement-pruning/emmental/modules/masked_nn.py | # coding=utf-8
# Copyright 2020-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 |
hf_public_repos/transformers/examples/research_projects/movement-pruning/emmental | hf_public_repos/transformers/examples/research_projects/movement-pruning/emmental/modules/__init__.py | from .binarizer import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
from .masked_nn import MaskedLinear
| 0 |
hf_public_repos/transformers/examples/research_projects/movement-pruning/emmental | hf_public_repos/transformers/examples/research_projects/movement-pruning/emmental/modules/binarizer.py | # coding=utf-8
# Copyright 2020-present, AllenAI Authors, University of Illinois Urbana-Champaign,
# Intel Nervana Systems 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 ... | 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/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/requirements.txt | faiss-cpu >= 1.7.2
datasets
psutil >= 5.9.1
torch >= 1.11.0
pytorch-lightning == 1.6.4
nvidia-ml-py3 == 7.352.0
ray >= 1.13.0 | 0 |
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/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/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/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 | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
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/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/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 | 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/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/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/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.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/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-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 | 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/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/longform-qa/requirements.txt | datasets >= 1.1.3
faiss-cpu
streamlit
elasticsearch
| 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/bert-loses-patience/test_run_glue_with_pabee.py | import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_with_pabee
from transformers.testing_utils import TestCasePlus
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger()
def get_setup_file():
parser = argparse.ArgumentParser()
parser.add_argument("-f")... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/bert-loses-patience/requirements.txt | transformers == 3.5.1 | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/bert-loses-patience/run_glue_with_pabee.py | # coding=utf-8
# Copyright 2020 The Google AI Language Team Authors, The HuggingFace Inc. team and Microsoft Corporation.
# 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.... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/bert-loses-patience/README.md | # Patience-based Early Exit
Patience-based Early Exit (PABEE) is a plug-and-play inference method for pretrained language models.
We have already implemented it on BERT and ALBERT. Basically, you can make your LM faster and more robust with PABEE. It can even improve the performance of ALBERT on GLUE. The only sacrifi... | 0 |
hf_public_repos/transformers/examples/research_projects/bert-loses-patience | hf_public_repos/transformers/examples/research_projects/bert-loses-patience/pabee/modeling_pabee_albert.py | # coding=utf-8
# Copyright 2020 Google AI, Google Brain, the HuggingFace Inc. team and Microsoft Corporation.
#
# 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/lic... | 0 |
hf_public_repos/transformers/examples/research_projects/bert-loses-patience | hf_public_repos/transformers/examples/research_projects/bert-loses-patience/pabee/modeling_pabee_bert.py | # coding=utf-8
# Copyright 2020 The Google AI Language Team Authors, The HuggingFace Inc. team and Microsoft Corporation.
# 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.... | 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_repos/transformers/examples/research_projects/bertology/requirements.txt | transformers == 3.5.1
| 0 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
hf_public_repos/transformers/examples/research_projects | hf_public_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 |
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/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 | 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/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/__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/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 | hf_public_repos/transformers/examples/legacy/run_language_modeling.py | #!/usr/bin/env python
# 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.
... | 0 |
hf_public_repos/transformers/examples | hf_public_repos/transformers/examples/legacy/run_camembert.py | #!/usr/bin/env python
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def fill_mask(masked_input, model, tokenizer, topk=5):
# Adapted from https://github.com/pytorch/fairseq/blob/master/fairseq/models/roberta/hub_interface.py
assert masked_input.count("<mask>") == 1
input_... | 0 |
hf_public_repos/transformers/examples | hf_public_repos/transformers/examples/legacy/run_transfo_xl.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University 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 co... | 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_openai_gpt.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University 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 co... | 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 |
hf_public_repos/transformers/examples | hf_public_repos/transformers/examples/legacy/run_swag.py | #!/usr/bin/env python
# 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.
... | 0 |
hf_public_repos/transformers/examples/legacy | hf_public_repos/transformers/examples/legacy/question-answering/run_squad.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 |
hf_public_repos/transformers/examples/legacy | hf_public_repos/transformers/examples/legacy/question-answering/README.md | #### Fine-tuning BERT on SQuAD1.0 with relative position embeddings
The following examples show how to fine-tune BERT models with different relative position embeddings. The BERT model
`bert-base-uncased` was pretrained with default absolute position embeddings. We provide the following pretrained
models which were ... | 0 |
hf_public_repos/transformers/examples/legacy | hf_public_repos/transformers/examples/legacy/question-answering/run_squad_trainer.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 |
hf_public_repos/transformers/examples/legacy | hf_public_repos/transformers/examples/legacy/multiple_choice/run_multiple_choice.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 |
hf_public_repos/transformers/examples/legacy | hf_public_repos/transformers/examples/legacy/multiple_choice/utils_multiple_choice.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 |
hf_public_repos/transformers/examples/legacy | hf_public_repos/transformers/examples/legacy/text-classification/run_tf_text_classification.py | #!/usr/bin/env python
# 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... | 0 |
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