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https://api.github.com/repos/huggingface/transformers/issues/14856 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14856/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14856/comments | https://api.github.com/repos/huggingface/transformers/issues/14856/events | https://github.com/huggingface/transformers/pull/14856 | 1,085,256,301 | PR_kwDOCUB6oc4wGnXH | 14,856 | [Generate] Remove attention_mask and integrate model_main_input_name | {
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"The changes to `Seq2SeqTrainer` also fix a problem with `predict_with_generate` for `VisionEncoderDecoder`.\r\n\r\nWith 4.15.0, setting `predict_with_generate=True`does not work with `VisionEncoderDecoder` and `Seq2SeqTrainer`.\r\n",
"Hey @cgawron,\r\n\r\nDo you have an issue with current master or is everything... | 1,640 | 1,641 | 1,640 | MEMBER | null | # What does this PR do?
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The `onnx` submodule does not use a lazy init like the other ones. This results in importing a given model/tokenzier/config, which imports OnnxConfig, initializing the onnx submodule completely, and in turn importing `PreTrainedModel` and `TFPreTrainedModel` (so PyTorch and TensorFlow).
Th... | {
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"@NielsRogge @LysandreJik Any updates/reasons not to merge this ?",
"@LysandreJik according to the [docs](https://pytorch.org/docs/stable/generated/torch.div.html) of PyTorch's torch.div:\r\n\r\n> \"floor\" - rounds the results of the division down. Equivalent to floor division in Python (the // operator)\r\n\r\... | 1,640 | 1,643 | 1,643 | CONTRIBUTOR | null | # What does this PR do?
Removes deprecation warning in LayoutLMV2 runs, caused by deprecated native floor divide.
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ x] Did you read the [contributor guideline](htt... | {
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https://api.github.com/repos/huggingface/transformers/issues/14852 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14852/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14852/comments | https://api.github.com/repos/huggingface/transformers/issues/14852/events | https://github.com/huggingface/transformers/pull/14852 | 1,085,106,179 | PR_kwDOCUB6oc4wGHmQ | 14,852 | Replace commit sha by commit url for update jobs | {
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As requested by @julien-c , this PR replaces the commit shas by the full urls in the update jobs:
- for the documentation
- for the transformers metadata dataset | {
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https://api.github.com/repos/huggingface/transformers/issues/14851 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14851/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14851/comments | https://api.github.com/repos/huggingface/transformers/issues/14851/events | https://github.com/huggingface/transformers/issues/14851 | 1,085,065,026 | I_kwDOCUB6oc5ArMdC | 14,851 | Fine-tune GPT-J with SageMaker Model Parallelism | {
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"Hi @joehoover -\r\n\r\nThanks for raising this issue! Couple of things based on the above configuration setup -\r\n\r\n1. Can you try with single instance training job with SMP configuration with partitions = number of devices, disable ddp by setting to False and set processes_per_host = <number of GPU devices> f... | 1,640 | 1,647 | 1,647 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.11.0
- Platform: SageMaker
- Python version: 3.8
- PyTorch version (GPU?): 1.9.0
- Using GPU in script?: ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14850 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14850/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14850/comments | https://api.github.com/repos/huggingface/transformers/issues/14850/events | https://github.com/huggingface/transformers/pull/14850 | 1,085,050,797 | PR_kwDOCUB6oc4wF8Jk | 14,850 | Convert docstrings of modeling files | {
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"Saw with @sgugger and the newline before `\"\"\"` isn't important and isn't liked by black.\r\n\r\nAs seen with Sylvain and Patrick, merging this PR now to prevent any conflicts - let's take a look at `master` once deployed to ensure everything works correctly.",
"From what I'm seeing, everything looks correct, ... | 1,640 | 1,640 | 1,640 | COLLABORATOR | null | # What does this PR do?
This is going to be a huge PR (sorry) but all modeling files have docstrings that are connected to the model outputs and the code samples in file_utils, so the conversion from rst to Markdown has to happen for all of those at the same time.
The doc-styler is commented out for now, as it ca... | {
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Fixes: https://github.com/huggingface/huggingface_hub/issues/550 | {
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This adds `WavLMForAudioFrameClassification` and `WavLMForXVector` as a follow-up to https://github.com/huggingface/transformers/pull/14723 | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,639 | 1,643 | 1,643 | NONE | null | Hello,
I have two similar questions. **First**, I'm trying to fine-tune the facebook/bart-large ([https://huggingface.co/facebook/bart-large](url)) but I want to train with 2 classes:
Example:
```
Text-input: "Hello, this text is about school and education."
Class 1: [X, Y, Z]
Class 2: [A, B, C]
Model answer... | {
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https://api.github.com/repos/huggingface/transformers/issues/14845 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14845/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14845/comments | https://api.github.com/repos/huggingface/transformers/issues/14845/events | https://github.com/huggingface/transformers/pull/14845 | 1,084,625,270 | PR_kwDOCUB6oc4wEjYx | 14,845 | [WavLM] Fix slow tests | {
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https://api.github.com/repos/huggingface/transformers/issues/14844 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14844/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14844/comments | https://api.github.com/repos/huggingface/transformers/issues/14844/events | https://github.com/huggingface/transformers/issues/14844 | 1,084,530,993 | I_kwDOCUB6oc5ApKEx | 14,844 | inconsistent BertTokenizer and BertTokenizerFast | {
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"- `transformers` version: 4.14.1\r\n- Platform: Darwin 20.3.0\r\n- Python version: 3.8.6\r\n- PyTorch version (GPU?): 1.10.1, no GPU\r\n\r\nUsing the below code, I was not able to reproduce the differences you show. The two tokenizers resulted in the same output. Maybe upgrade `transformers` and clear your `transf... | 1,639 | 1,648 | 1,648 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.12.5
- Platform: centos
- Python version: 3.7.6
- PyTorch version (GPU?): CPU
- Tensorflow version (GPU?)... | {
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https://api.github.com/repos/huggingface/transformers/issues/14843 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14843/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14843/comments | https://api.github.com/repos/huggingface/transformers/issues/14843/events | https://github.com/huggingface/transformers/issues/14843 | 1,084,437,832 | I_kwDOCUB6oc5AozVI | 14,843 | T5ForConditionalGeneration lm_head not initialized from pretrained checkpoint | {
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"Hey @ZhaofengWu, \r\n\r\nFor all encoder-decoder models, such as T5, Bart, ..., the `lm_head` of the decoder is shared between the decoder input word embedding if `tie_word_embeddings` is set to `True` in the model's config. You can check the config for `t5-small` [here](https://huggingface.co/t5-small/blob/main/c... | 1,639 | 1,640 | 1,640 | CONTRIBUTOR | null | It seems that pretrained T5 checkpoints such as `"t5-small"`, `"t5-base"`, etc., do not contain the `lm_head` parameter.
https://github.com/huggingface/transformers/blob/84ea427f460ffc8d2ddc08a341ccda076c24fc1f/src/transformers/models/t5/modeling_t5.py#L1434-L1438
@patrickvonplaten explained in #3553 that these three... | {
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https://api.github.com/repos/huggingface/transformers/issues/14842 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14842/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14842/comments | https://api.github.com/repos/huggingface/transformers/issues/14842/events | https://github.com/huggingface/transformers/pull/14842 | 1,084,397,779 | PR_kwDOCUB6oc4wD0Nn | 14,842 | Fix dead link to benchmarks.ipynb | {
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# What does this PR do?
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"You are using `save_strategy=\"no\"`, so, as requested, the model is not saved. You can add a line `trainer.save_model(xxx)` to manually save it after the training.",
"@sgugger I corrected it to `save_strategy=\"epoch\"` and it saves model with every epoch with numbers like `checkpoint-12250, checkpoint-915` so... | 1,639 | 1,640 | 1,640 | NONE | null | I am downloading the model <https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384/tree/main> **microsoft/Multilingual-MiniLM-L12-H384** and then using it.
Transformer Version: '4.11.3'
**I have written the below code:**
```
model = tr.BertForSequenceClassification.from_pretrained("/home/pc/minilm_mode... | {
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https://api.github.com/repos/huggingface/transformers/issues/14840 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14840/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14840/comments | https://api.github.com/repos/huggingface/transformers/issues/14840/events | https://github.com/huggingface/transformers/issues/14840 | 1,084,333,929 | I_kwDOCUB6oc5AoZ9p | 14,840 | trainer.create_model_card should be run by process 0 only in distributed training | {
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"Thanks for flagging! Adding some logic for that in the PR mentioned above."
] | 1,639 | 1,640 | 1,640 | NONE | null | ### Who can help
@gchhablani, @sgugger
## Information
Trainer.create_model_card() does not check which process is running. In distributed training, all processes would try to write into $output_dir/README.md and sometimes cause crashes.
The problem arises when using run_clm.py in distributed training.
## T... | {
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https://api.github.com/repos/huggingface/transformers/issues/14839 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14839/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14839/comments | https://api.github.com/repos/huggingface/transformers/issues/14839/events | https://github.com/huggingface/transformers/issues/14839 | 1,084,225,023 | I_kwDOCUB6oc5An_X_ | 14,839 | Fine-tuning GPT-J-6B in colab: 8-bit weights with low-rank adaptors | {
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"Just read the LORA paper and your implementation combined with weight quantization is very neat, @deniskamazur. Thank you!\r\n\r\na few comments:\r\n\r\n1. If and when this is integrated into transformers may I just suggest not to override `__repr__` in the frozen modules? I have puzzled for a while over why the `... | 1,639 | 1,682 | null | NONE | null | # 🌟 New model addition
## Model description
This is a version of EleutherAI's GPT-J with 6 billion parameters that is modified so you can generate and fine-tune the model in colab or equivalent desktop GPU (e.g. single 1080Ti).
The original GPT-J takes 22+ GB memory for float32 parameters. Even if you cast ev... | {
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https://api.github.com/repos/huggingface/transformers/issues/14838 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14838/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14838/comments | https://api.github.com/repos/huggingface/transformers/issues/14838/events | https://github.com/huggingface/transformers/issues/14838 | 1,084,217,880 | I_kwDOCUB6oc5An9oY | 14,838 | Subword Tokenization Bug after Non-Space Word Boundaries (AlbertTokenizerFast) | {
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"cc @SaulLu ",
"Hi @mcrchopra ,\r\n\r\nCould you tell us more about why you think the tokenization of `(presentation)` with Albert's tokenizer should be `'(', '▁presentation', ')'` and not `'(', 'present', 'ation', ')'`? \r\n\r\nApriori, there is no reason to have similar tokenizations produced with Albert's and ... | 1,639 | 1,640 | 1,640 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.11.0
- Platform: macOS Big Sur
- Python version: 3.8.5
### Who can help
@LysandreJik
## Information
... | {
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https://api.github.com/repos/huggingface/transformers/issues/14837 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14837/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14837/comments | https://api.github.com/repos/huggingface/transformers/issues/14837/events | https://github.com/huggingface/transformers/pull/14837 | 1,084,179,501 | PR_kwDOCUB6oc4wDH5x | 14,837 | Adding S4 Model | {
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"@kamalkraj This looks great! Please let us know if you're encountering any problems, and of course ping me when it's ready for a final review.",
"Hi @kamalkraj ! We noticed there haven't been any commits here for a while - do you want us to find someone to take it over and resolve the issues from here? Either wa... | 1,639 | 1,664 | 1,647 | CONTRIBUTOR | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/14836 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14836/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14836/comments | https://api.github.com/repos/huggingface/transformers/issues/14836/events | https://github.com/huggingface/transformers/issues/14836 | 1,084,152,217 | I_kwDOCUB6oc5AntmZ | 14,836 | Segmentation fault (core dumped) when conversion of GPT-J to onnx | {
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"I figured out the above reason. While ONNXconfig file is wrong, I explicit use of GPU, leading to segmentation fault. \r\nCorrect config is here\r\n```\r\nclass GPTJOnnxConfig(OnnxConfig):\r\n @property\r\n def inputs(self) -> Mapping[str, Mapping[int, str]]:\r\n return OrderedDict(\r\n [\r... | 1,639 | 1,642 | 1,642 | NONE | null | ## Environment info
- `transformers` version: 4.14.1
- `PyTorch` version:
```
nvidia-dlprof-pytorch-nvtx 1.7.0
pytorch-quantization 2.1.2
torch 1.11.0a0+b6df043
torch-tensorrt 1.0.0a0
torchtext 0.12.0a0
torchvision 0.11... | {
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https://api.github.com/repos/huggingface/transformers/issues/14835 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14835/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14835/comments | https://api.github.com/repos/huggingface/transformers/issues/14835/events | https://github.com/huggingface/transformers/pull/14835 | 1,084,143,380 | PR_kwDOCUB6oc4wDBKZ | 14,835 | Update CONTRIBUTING.md | {
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# What does this PR do?
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, pleas... | {
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https://api.github.com/repos/huggingface/transformers/issues/14834 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14834/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14834/comments | https://api.github.com/repos/huggingface/transformers/issues/14834/events | https://github.com/huggingface/transformers/issues/14834 | 1,084,130,824 | I_kwDOCUB6oc5AnoYI | 14,834 | eval_loss is nan for GPT2 trained with fp16 + deepseed on 8xA40s | {
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"Maybe of interest to @stas00 ",
"Thank you, @LysandreJik, for the ping. The issue template does say to tag me on Deepspeed issues.\r\n\r\nYes, @aqred1, you're running into overflow and yes Deepspeed should assert there as I proposed here: https://github.com/microsoft/DeepSpeed/issues/1599 But it's not a bug per ... | 1,639 | 1,640 | 1,640 | NONE | null | Hi,
I'm training GPT2 from scratch. After 5 epochs, the training loss decreased dramatically and the eval loss became nan. The last steps during training all produce the same logs:
```
[2021-12-19 16:54:45,098] [INFO] [unfused_optimizer.py:275:_update_scale] Grad overflow on iteration: 445299
[2021-12-19 16:54:4... | {
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https://api.github.com/repos/huggingface/transformers/issues/14833 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14833/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14833/comments | https://api.github.com/repos/huggingface/transformers/issues/14833/events | https://github.com/huggingface/transformers/issues/14833 | 1,084,109,237 | I_kwDOCUB6oc5AnjG1 | 14,833 | Seq2SeqTrainer.evaluation_loop requires `labels` due to DataCollatorForSeq2Seq | {
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"Good catch! The `DataCollatorForSeq2Seq` should check for `None` `labels` before computing `decoder_input_ids`,\r\nWould you like to open a PR to fix this? Happy to help with it, thanks !",
"I would have opened a PR, but there seem to have more in it. Modifying `DataCollatorForSeq2Seq` solved the issue for a BA... | 1,639 | 1,643 | 1,643 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.11.0.dev0
- Platform: Linux-3.10.0-1160.49.1.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.8.11
- PyTorch version (GPU?): 1.9.0+cu102 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: no... | {
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https://api.github.com/repos/huggingface/transformers/issues/14832 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14832/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14832/comments | https://api.github.com/repos/huggingface/transformers/issues/14832/events | https://github.com/huggingface/transformers/pull/14832 | 1,084,042,079 | PR_kwDOCUB6oc4wCtt6 | 14,832 | Fix the wrong attention mask in TransformerXL by shifting `mask_shift_len` with 1 | {
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"Thanks a lot for your PR @tanchihpin0517. @TevenLeScao - could you maybe take a look here, I think you've added this part of the code a while back",
"Hey @tanchihpin0517 , if this is correct, I am surprised that it didn't show up in generation before. Have you noticed erroneous generation with TransformerXL in t... | 1,639 | 1,653 | 1,653 | NONE | null | # What does this PR do?
In `forward` of TransformerXL, the attention mask `dec_attn_mask` is set up by:
```
dec_attn_mask = (torch.triu(all_ones, 1 + mlen) + torch.tril(all_ones, -mask_shift_len))[:, :, None] # -1
```
But I noticed if `mask_shift_len` is zero (while the default memory length equals to the i... | {
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https://api.github.com/repos/huggingface/transformers/issues/14831 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14831/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14831/comments | https://api.github.com/repos/huggingface/transformers/issues/14831/events | https://github.com/huggingface/transformers/issues/14831 | 1,084,027,253 | I_kwDOCUB6oc5AnPF1 | 14,831 | FlaxVisionEncoderDecoderModel has no attribute 'from_encoder_decoder_pretrained' ? | {
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"I think this is because `flax` is not installed, for flax models we should install `jax`, `jaxlib` and `flax`. The import returns a dummy `FlaxVisionEncoderDecoderModel` when flax is not installed which has no methods.\r\n\r\nYou could see in this colab that it works https://colab.research.google.com/drive/1g6oU-A... | 1,639 | 1,640 | 1,640 | NONE | null | Transformers Version: 4.14.1
`FlaxVisionEncoderDecoderModel.from_encoder_decoder_pretrained('google/vit-base-patch32-224-in21k', 'gpt2')`
throws the following error
`AttributeError: type object 'FlaxVisionEncoderDecoderModel' has no attribute 'from_encoder_decoder_pretrained'`
But the documentation below su... | {
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https://api.github.com/repos/huggingface/transformers/issues/14830 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14830/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14830/comments | https://api.github.com/repos/huggingface/transformers/issues/14830/events | https://github.com/huggingface/transformers/issues/14830 | 1,084,011,087 | I_kwDOCUB6oc5AnLJP | 14,830 | Adafactor lacking min_dim_size_to_factor | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,639 | 1,643 | 1,643 | CONTRIBUTOR | null | The Adafactor implementation in mesh_tensorflow has a `min_dim_size_to_factor` flag where tensors with size smaller than this will not be factored.
https://github.com/tensorflow/mesh/blob/57ed4018e6a173952501b074daabad32b6449f3d/mesh_tensorflow/optimize.py#L220
However, this flag is lacking in HF's version. And the... | {
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https://api.github.com/repos/huggingface/transformers/issues/14829 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14829/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14829/comments | https://api.github.com/repos/huggingface/transformers/issues/14829/events | https://github.com/huggingface/transformers/pull/14829 | 1,083,978,104 | PR_kwDOCUB6oc4wChKl | 14,829 | [Wav2Vec2 Phoneme] Let phonemizer lang default to tokenizer's settings | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/14828 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14828/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14828/comments | https://api.github.com/repos/huggingface/transformers/issues/14828/events | https://github.com/huggingface/transformers/issues/14828 | 1,083,962,655 | I_kwDOCUB6oc5Am_Uf | 14,828 | Unable to save pretrained model after finetuning : trainer.save_pretrained(modeldir) AttributeError: 'Trainer' object has no attribute 'save_pretrained' | {
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"not sure where you took that code from, but indeed the Trainer doesn't have such method.\r\n\r\nWhat you want is:\r\n\r\n```\r\nmodel.save_pretrained(modeldir)\r\n```\r\n",
"Or `trainer.save_model(modeldir)` which will call the method Stas mentioned.",
"Hey folks, i couldn't get [`save_model`](https://huggingf... | 1,639 | 1,694 | 1,639 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.8
- Platform:
- Python version: 3.9
- PyTorch version (GPU?): 1.9.0
- Tensorflow version (GPU?):
- Using... | {
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https://api.github.com/repos/huggingface/transformers/issues/14827 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14827/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14827/comments | https://api.github.com/repos/huggingface/transformers/issues/14827/events | https://github.com/huggingface/transformers/issues/14827 | 1,083,927,388 | I_kwDOCUB6oc5Am2tc | 14,827 | as_target_tokenizer is not an attribute of PreTrainedTokenizerBase and Bart/RobertaTokenizer | {
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"Hello! The `as_target_tokenizer` method is specifically for seq2seq models in order to separate between the source and target tokenizers. Why do you need it for RoBERTa?\r\n\r\ncc @patrickvonplaten @sgugger ",
"I would double-check on v4.14.1 as every tokenizer has this method (it just doesn't do anything for mo... | 1,639 | 1,643 | 1,643 | NONE | null | ### Environment
Instance: Paperspace Gradient Cloud Instance
transformers: 3.5.1 (same issue on 4.14.1)
Python: 3.6.9
### Information
When creating an instance of the Roberta/Bart tokenizer the method as_target_tokenizer is not recognized. Code almost entirely the same as in the summarization example of Huggingf... | {
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https://api.github.com/repos/huggingface/transformers/issues/14826 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14826/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14826/comments | https://api.github.com/repos/huggingface/transformers/issues/14826/events | https://github.com/huggingface/transformers/pull/14826 | 1,083,856,453 | PR_kwDOCUB6oc4wCJAF | 14,826 | Add support for TPU training with CodeParrot! | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,639 | 1,644 | 1,644 | CONTRIBUTOR | null | # What does this PR do?
This PR adds support for training CodeParrot-style models on TPUs! It also fixes a small issue in the model initialization script.
You can verify it works using this colab notebook: https://colab.research.google.com/drive/143qMz_0yf1Irb1ZrsYIWu39nqBYh9OTd?usp=sharing
## Before submittin... | {
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https://api.github.com/repos/huggingface/transformers/issues/14825 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14825/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14825/comments | https://api.github.com/repos/huggingface/transformers/issues/14825/events | https://github.com/huggingface/transformers/issues/14825 | 1,083,818,043 | I_kwDOCUB6oc5AmcA7 | 14,825 | Flax/Roberta - Tokenizer | {
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"Note that tokenizers are independent of the framework, so flax/pytorch shouldn't make any difference. \r\n\r\n> My initial tests indicates that it also can mess up the Flax training\r\n\r\nWhat do you mean by it can mess up the flax training ?\r\n\r\nIs there any difference any tokenization when you use `AutoToken... | 1,639 | 1,652 | 1,652 | CONTRIBUTOR | null | ## Environment info
transformers version: 4.14.0.dev0
Platform: Linux-5.4.0-1043-gcp-x86_64-with-glibc2.29
Python version: 3.8.10
Flax version (CPU?/GPU?/TPU?): 0.3.4 (cpu)
Jax version: 0.2.17
JaxLib version: 0.1.68
### Who can help
@patrickvonplaten, @patil-suraj, @LysandreJik
## Information
I am reporti... | {
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https://api.github.com/repos/huggingface/transformers/issues/14824 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14824/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14824/comments | https://api.github.com/repos/huggingface/transformers/issues/14824/events | https://github.com/huggingface/transformers/issues/14824 | 1,083,815,011 | I_kwDOCUB6oc5AmbRj | 14,824 | preprocessing_num_workers coredump | {
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"Is this related to the flax script or does the core dump also occur when you just process the dataset? Could you maybe write a script to just process the dataset and see if it gives a core dump, so we could pinpoint the issue? Thanks!",
"@patil-suraj Thanks for the feedback. \r\n\r\nI did not have the possibilit... | 1,639 | 1,643 | 1,643 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.14.0.dev0
- Platform: Linux-5.4.0-1043-gcp-x86_64-with-glibc2.29
- Python version: 3.8.10
- Flax version (CPU?/GPU?/TPU?): 0.3.4 (cpu)
- Jax version: 0.2.17
- JaxLib version: 0.1.68
### Who can help
@patrickvonplaten
@patil-suraj
## Information
I am trai... | {
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https://api.github.com/repos/huggingface/transformers/issues/14823 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14823/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14823/comments | https://api.github.com/repos/huggingface/transformers/issues/14823/events | https://github.com/huggingface/transformers/issues/14823 | 1,083,786,153 | I_kwDOCUB6oc5AmUOp | 14,823 | How to use Roberta as the Encoder and a randomly initialized TransformerDecoder as the Decoder? | {
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"Hey @Captainr22, \r\n\r\nI would recommend doing the following:\r\n\r\n- 1) Create a randomly intialized `RobertaModel` as your transformer decoder:\r\n```python\r\nfrom transformers import RobertaModel, RobertaConfig\r\n\r\ndecoder = RobertaModel(RobertaConfig(num_layers=4))\r\ndecoder.save_pretrained(\"./temp\")... | 1,639 | 1,640 | 1,640 | NONE | null | Hello！
I want to use Roberta as an Encoder and a randomly initialized TransformerDecoder as a Decoder. I know EncoderDecoderModel can make any pretrained autoencoding model as the encoder and any pretrained autoregressive model as the decoder. But I just want to use 4 or 6 TransformerDecoder layers as my decoder.
Ma... | {
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https://api.github.com/repos/huggingface/transformers/issues/14822 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14822/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14822/comments | https://api.github.com/repos/huggingface/transformers/issues/14822/events | https://github.com/huggingface/transformers/issues/14822 | 1,083,723,778 | I_kwDOCUB6oc5AmFAC | 14,822 | fp16 flag silently fails | {
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"It's not an issue of GPU not supporting fp16. It's an issue of many models trained in bf16 and attempted to be used with fp16 and overflowing due to the incompatible numerical range. bf16-pretrained models use much bigger weight values than fp16 can accommodate so it overflows.\r\n\r\nPlease see: https://github.co... | 1,639 | 1,643 | 1,643 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.15.0.dev0
- Platform: Linux-5.10.68+-x86_64-with-debian-bullseye-sid
- Python version: 3.7.12
- PyTorch ve... | {
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https://api.github.com/repos/huggingface/transformers/issues/14821 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14821/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14821/comments | https://api.github.com/repos/huggingface/transformers/issues/14821/events | https://github.com/huggingface/transformers/pull/14821 | 1,083,701,647 | PR_kwDOCUB6oc4wBsTi | 14,821 | Add 'with torch.no_grad()' to DeBERTa integration test forward pass | {
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As proposed in #14642, this encapsulates the forward pass in the DeBERTa integration test with "with torch.no_grad():". This way, no unnecessary gradients are computed during inference.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14820 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14820/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14820/comments | https://api.github.com/repos/huggingface/transformers/issues/14820/events | https://github.com/huggingface/transformers/pull/14820 | 1,083,693,460 | PR_kwDOCUB6oc4wBqoo | 14,820 | Add 'with torch.no_grad()' to BERT integration test forward pass | {
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As proposed in #14642, this encapsulates the forward pass in the BERT integration test with "with torch.no_grad():". This way, no unnecessary gradients are computed during inference.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14819 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14819/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14819/comments | https://api.github.com/repos/huggingface/transformers/issues/14819/events | https://github.com/huggingface/transformers/issues/14819 | 1,083,650,111 | I_kwDOCUB6oc5AlzA_ | 14,819 | RFC: Integrating bitsandbytes 8-bit optimizer / adding Embedding Norm | {
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"Regarding the optimizers for `Trainer`, I think we can have a \"small\" breaking change in general and completely remove our implementation of AdamW and instead make use of `torch's` native `AdamW` implementation. \r\n\r\nI think it's a good idea to add a `--optim` arg to Trainer",
"Regarding the StableEmbedding... | 1,639 | 1,650 | 1,650 | CONTRIBUTOR | null | # 🚀 Feature request
1. **BNB** AdamW Optimizer: https://github.com/facebookresearch/bitsandbytes created by @TimDettmers uses 8-bit quantization technique, which allows to reduce memory usage for the AdamW optimizer from 8 bytes to 2 bytes, which is a huge memory saving and I think our users will benefit a lot from... | {
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https://api.github.com/repos/huggingface/transformers/issues/14818 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14818/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14818/comments | https://api.github.com/repos/huggingface/transformers/issues/14818/events | https://github.com/huggingface/transformers/issues/14818 | 1,083,630,809 | I_kwDOCUB6oc5AluTZ | 14,818 | a | {
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https://api.github.com/repos/huggingface/transformers/issues/14817 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14817/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14817/comments | https://api.github.com/repos/huggingface/transformers/issues/14817/events | https://github.com/huggingface/transformers/issues/14817 | 1,083,629,254 | I_kwDOCUB6oc5Alt7G | 14,817 | Roberta Classification Head | {
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"Hi! We try to stick as much as possible to the original implementation. See fairseq's original implementation here: https://github.com/pytorch/fairseq/blob/a54021305d6b3c4c5959ac9395135f63202db8f1/fairseq/models/roberta/model.py#L394-L429",
"Thank you so much. "
] | 1,639 | 1,640 | 1,640 | NONE | null | Why does Roberta classification Head uses 2 linear layers? https://github.com/huggingface/transformers/blob/84ea427f460ffc8d2ddc08a341ccda076c24fc1f/src/transformers/models/roberta/modeling_roberta.py#L1443
The BERT classification head uses only one and it makes sense since all the work is done by the Transformer l... | {
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https://api.github.com/repos/huggingface/transformers/issues/14816 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14816/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14816/comments | https://api.github.com/repos/huggingface/transformers/issues/14816/events | https://github.com/huggingface/transformers/pull/14816 | 1,083,554,460 | PR_kwDOCUB6oc4wBNhu | 14,816 | [examples/summarization] deal with None in data records | {
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"As I said before, the examples are not supposed to work out of the box on every dataset and we shouldn't strive for that. Adding more complexity should be on the user's side when they want to deal with another dataset. Cf the second paragraph of the examples README:\r\n\r\n> While we strive to present as many use ... | 1,639 | 1,640 | 1,640 | CONTRIBUTOR | null | When trying to use https://huggingface.co/datasets/wikihow with `run_summarization.py` I run into incomplete records in the manually downloaded dataset (the data is not on the hub and requires a user to download it manually):
```
[...]
File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/arrow_datas... | {
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https://api.github.com/repos/huggingface/transformers/issues/14815 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14815/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14815/comments | https://api.github.com/repos/huggingface/transformers/issues/14815/events | https://github.com/huggingface/transformers/pull/14815 | 1,083,307,481 | PR_kwDOCUB6oc4wAZO- | 14,815 | [Generate] Correct input_ids detection | {
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"Thanks for fixing!"
] | 1,639 | 1,639 | 1,639 | MEMBER | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/14814 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14814/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14814/comments | https://api.github.com/repos/huggingface/transformers/issues/14814/events | https://github.com/huggingface/transformers/issues/14814 | 1,083,293,398 | I_kwDOCUB6oc5Akb7W | 14,814 | Support on Mixture of expert models | {
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"Hi,\r\n\r\nIt's true, but as long as there are no pretrained weights, chances are small models are added. There are some open-source implementations of MoE available, including:\r\n\r\n- DeepSpeed: https://www.deepspeed.ai/tutorials/mixture-of-experts/\r\n- Fairseq.\r\n\r\nOnce there are some pretrained weights av... | 1,639 | 1,650 | null | NONE | null | Hi, I find that there are emerging works in the field of NLP on **Mixture of experts** based models, such as Switch Transformers from Google. However, I do not find such mixture of expert models in huggingface transformers. Do you have the plan to support such models? Thanks ! | {
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https://api.github.com/repos/huggingface/transformers/issues/14813 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14813/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14813/comments | https://api.github.com/repos/huggingface/transformers/issues/14813/events | https://github.com/huggingface/transformers/pull/14813 | 1,083,255,874 | PR_kwDOCUB6oc4wAOOp | 14,813 | [Perceiver] Skip multi-gpu tests for now | {
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"Merging now as it's blocking the failing tests a bit. In a follow-up PR we should enable DDP as well "
] | 1,639 | 1,640 | 1,640 | MEMBER | null | # What does this PR do?
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,639 | 1,666 | 1,665 | MEMBER | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
As discussed on the [forums](https://discuss.huggingface.co/t/can-i-export-a-visionencoderdecoder-checkpoint-to-onnx/12885), it would be nice if one could ex... | {
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"Thanks for fixing!"
] | 1,639 | 1,639 | 1,639 | MEMBER | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/14810 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14810/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14810/comments | https://api.github.com/repos/huggingface/transformers/issues/14810/events | https://github.com/huggingface/transformers/pull/14810 | 1,083,030,475 | PR_kwDOCUB6oc4v_eKI | 14,810 | Fix Perceiver multi GPU test | {
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This PR fixes the failing test on CI for Perceiver on multi-GPU.
Note: I can't run this test locally, unfortunately, so I hope it'll pass. | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,639 | 1,643 | 1,643 | CONTRIBUTOR | null | As the title, I haven't found the way to share input embeddings in self.decoder.weight.
Can someone help me point it out.?
```python
class BertLMPredictionHead(nn.Module):
def __init__(self, config):
super().__init__()
self.transform = BertPredictionHeadTransform(config)
# The o... | {
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https://api.github.com/repos/huggingface/transformers/issues/14808 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14808/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14808/comments | https://api.github.com/repos/huggingface/transformers/issues/14808/events | https://github.com/huggingface/transformers/pull/14808 | 1,082,700,414 | PR_kwDOCUB6oc4v-Z0K | 14,808 | Add 'with torch.no_grad()' to ALBERT integration test forward pass | {
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As proposed in #14642, this encapsulates the forward pass in the ALBERT integration test with "with torch.no_grad():".
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [X] Did you read the [contributor guideline... | {
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"Hey Steven, I believe there was an issue in your merge/rebase and GitHub is having a hard time understanding what happened. Could you close and reopen a new PR without touching at your branch so that we may see the actual differences? Thank you."
] | 1,639 | 1,643 | 1,641 | MEMBER | null | # What does this PR do?
This PR contains the first draft of the Get Started docs as discussed for the new Transformers IA. Some additional thoughts:
- I think adding better signposts on the landing page will help users quickly get to the content they are looking for. For inspiration, maybe we can have cards like ... | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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"I'm not sure what section of the dataset it was eval'ed on so it's hard to tell how to compare the scores, especially if the dataset has grown since it was eval'ed on a year ago.\r\n\r\nSo first I had to do the following as the dataset contains missing fields:\r\n\r\n```\r\ndiff --git a/examples/pytorch/summarizat... | 1,639 | 1,643 | 1,643 | NONE | null | # 🖥 Benchmarking `transformers`
## Benchmark
Which part of `transformers` did you benchmark?
[```google/pegasus-wikihow```](https://huggingface.co/google/pegasus-wikihow)
## Set-up
What did you run your benchmarks on? Please include details, such as: CPU, GPU? If using multiple GPUs, which parallelization... | {
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This PR adds a new attribute to all models called `main_input_name` which allows us to know whether the model expects `input_ids`, `pixel_values`, `input_values` or `input_features` as a first argument. A test is also added to check the correct value is set for all models, by inspecting the s... | {
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https://api.github.com/repos/huggingface/transformers/issues/14802 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14802/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14802/comments | https://api.github.com/repos/huggingface/transformers/issues/14802/events | https://github.com/huggingface/transformers/pull/14802 | 1,082,506,884 | PR_kwDOCUB6oc4v9wzN | 14,802 | [Seq2SeqTrainer] Remove model input name hack | {
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https://api.github.com/repos/huggingface/transformers/issues/14801 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14801/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14801/comments | https://api.github.com/repos/huggingface/transformers/issues/14801/events | https://github.com/huggingface/transformers/pull/14801 | 1,082,468,238 | PR_kwDOCUB6oc4v9onn | 14,801 | [ImageGPT] Deprecate pixel_values input name to input_ids | {
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"> LGTM. Can you verify the slow integration test is passing in `test_modeling_imagegpt.py`?\r\n\r\nAll tests are passing"
] | 1,639 | 1,639 | 1,639 | MEMBER | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/14800 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14800/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14800/comments | https://api.github.com/repos/huggingface/transformers/issues/14800/events | https://github.com/huggingface/transformers/pull/14800 | 1,082,347,413 | PR_kwDOCUB6oc4v9OzH | 14,800 | Update CONTRIBUTING.md | {
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# What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/14799 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14799/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14799/comments | https://api.github.com/repos/huggingface/transformers/issues/14799/events | https://github.com/huggingface/transformers/pull/14799 | 1,082,274,143 | PR_kwDOCUB6oc4v8-wu | 14,799 | Update CONTRIBUTING.md | {
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# What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/14798 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14798/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14798/comments | https://api.github.com/repos/huggingface/transformers/issues/14798/events | https://github.com/huggingface/transformers/issues/14798 | 1,082,264,973 | I_kwDOCUB6oc5Agg2N | 14,798 | CUDA error: device-side assert triggered while training Marian MT | {
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"It's sadly impossible for us to reproduce this error give the message above. From the error message, I'm quite sure that you are using a sequence length which is too long. Could you make sure you cut the input sequences to the maximum length of Marian?",
"@patrickvonplaten Thanks for the reply. From the logs, i... | 1,639 | 1,642 | 1,642 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: transformers-4.13.0.dev0
- Platform: linux
- Python version: 3.8
- PyTorch version (GPU?): torch==1.11.0a0+b... | {
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https://api.github.com/repos/huggingface/transformers/issues/14797 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14797/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14797/comments | https://api.github.com/repos/huggingface/transformers/issues/14797/events | https://github.com/huggingface/transformers/issues/14797 | 1,082,258,256 | I_kwDOCUB6oc5AgfNQ | 14,797 | Unable so save quantized model for mobile using Speech2Text | {
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"We don't fully support torch quantization in `transformers`. Did you try out the optimum library instead: https://github.com/huggingface/optimum . Also gently pinging @michaelbenayoun @echarlaix @lewtun here",
"Hi @stefan-falk! As @patrickvonplaten mentioned, we don't support native torch quantization. However w... | 1,639 | 1,642 | 1,642 | NONE | null | ## Environment info
- Platform: Ubuntu 20.04
- Python version: 3.9
- PyTorch version (GPU?): 1.10.0 (yes)
### Who can help
@patrickvonplaten @anton-l
## Information
I am trying to save a quantized model for speech recognition. Nothing fancy, I'm just trying to explore 🤗 for this topic hoping I can ge... | {
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https://api.github.com/repos/huggingface/transformers/issues/14796 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14796/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14796/comments | https://api.github.com/repos/huggingface/transformers/issues/14796/events | https://github.com/huggingface/transformers/pull/14796 | 1,082,256,465 | PR_kwDOCUB6oc4v868- | 14,796 | Train step fix | {
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https://api.github.com/repos/huggingface/transformers/issues/14795 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14795/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14795/comments | https://api.github.com/repos/huggingface/transformers/issues/14795/events | https://github.com/huggingface/transformers/pull/14795 | 1,082,218,757 | PR_kwDOCUB6oc4v8zA8 | 14,795 | Remove `require_datasets` testing utility | {
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https://api.github.com/repos/huggingface/transformers/issues/14794 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14794/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14794/comments | https://api.github.com/repos/huggingface/transformers/issues/14794/events | https://github.com/huggingface/transformers/issues/14794 | 1,082,195,643 | I_kwDOCUB6oc5AgP67 | 14,794 | some error when I run the pytorch example wav2vec2 by rum_common_voice.py | {
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when I went to the web https://huggingface.co in browser, I found that the page https://huggingface.co/api/ is 404.
Has the structure of https://huggingface.co changed? and what... | {
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https://api.github.com/repos/huggingface/transformers/issues/14793 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14793/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14793/comments | https://api.github.com/repos/huggingface/transformers/issues/14793/events | https://github.com/huggingface/transformers/issues/14793 | 1,082,167,288 | I_kwDOCUB6oc5AgI_4 | 14,793 | Can I print mlm and nsp loss instead of their sum while train the BertForPretraning model? | {
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"Hey @dancingpipi! There's no way to get the individual losses out of the box, but you could use the returned logits with your labels to calculate the two losses out of the model.\r\n\r\nThe loss is computed as such:\r\n\r\n```\r\n if labels is not None and next_sentence_label is not None:\r\n los... | 1,639 | 1,642 | 1,642 | CONTRIBUTOR | null | The loss just contain the sum of nsp and mlm loss, I want to know their respective specific values
Is there a way to do that? | {
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https://api.github.com/repos/huggingface/transformers/issues/14792 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14792/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14792/comments | https://api.github.com/repos/huggingface/transformers/issues/14792/events | https://github.com/huggingface/transformers/pull/14792 | 1,082,097,510 | PR_kwDOCUB6oc4v8ZoJ | 14,792 | Add Speech Seq2Seq Training script | {
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"Hmmm, not that easy the training it seems...will run some more examples next week with Wav2Vec2 - BERT",
"Getting good results now for wav2vec2 - bart: https://huggingface.co/patrickvonplaten/wav2vec2-2-bart-base",
"Results are good: https://huggingface.co/models?other=asr_seq2esq \r\n\r\nCleaning up the PR an... | 1,639 | 1,640 | 1,640 | MEMBER | null | # What does this PR do?
<!--
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"Hello, thanks for opening an issue! For an additional chance of getting your question answered, could you ask your question on the [forum](https://discuss.huggingface.co) as well, to involve the broader community?\r\n\r\nThanks!",
"This issue has been automatically marked as stale because it has not had recent a... | 1,639 | 1,642 | 1,642 | CONTRIBUTOR | null | Hey everyone!
I just tried the example code `transformers/examples/pytorch/summarization/run_summarization_no_trainer.py` but got 100.0 for eval rouge1, rouge2, and rougeL on a GEM dataset. Seems like there is something wrong here. Am I missing something? (Tagging @patil-suraj as it involves summarization)
My scr... | {
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https://api.github.com/repos/huggingface/transformers/issues/14790 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14790/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14790/comments | https://api.github.com/repos/huggingface/transformers/issues/14790/events | https://github.com/huggingface/transformers/pull/14790 | 1,081,487,634 | PR_kwDOCUB6oc4v6Zc0 | 14,790 | Post sphinx-clean up and contributing guide updates | {
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This PR finishes to clean up some old references to sphinx in the setup or Makefile and updates the contributing guide/docs README to explain to users how to build the docs with our new tool or how to write them.
Fixes #14762 | {
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"Yeah that would be quite nice! cc @Narsil ",
"Hi @dunalduck0 ,\r\n\r\nIf you use a `Dataset` instead of a list, it will work.\r\n\r\n```python\r\ndataset = MyDataset()\r\n\r\nfor out in tqdm.tqdm(pipe(dataset)):\r\n print(out)\r\n```\r\n\r\nAnd converting a raw list to a dataset is relatively easy\r\n\r\n```p... | 1,639 | 1,642 | 1,642 | NONE | null | # 🚀 Feature request
Pipeline can process a list of inputs but doesn't print out progress. If the input list is large, it's difficult to tell whether the pipeline is running fine or gets stuck. Add tqdm to the generation loop to show progress.
For example, if I add tqdm to /src/transformers/pipelines/base.py line... | {
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https://api.github.com/repos/huggingface/transformers/issues/14788 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14788/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14788/comments | https://api.github.com/repos/huggingface/transformers/issues/14788/events | https://github.com/huggingface/transformers/pull/14788 | 1,081,423,332 | PR_kwDOCUB6oc4v6Neh | 14,788 | Fix the build documentation job | {
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The last two releases were not automatically documented. That's fine for v4.14.0 since we yanked it, and I did a manual update for v4.14.1, but in the future it would be nice to not have to do this!
The first fix is to make sure Transformers is installed from the current checked out branch... | {
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Urgent fix to make the TensorFlow side of the library work agian when Onnx is installed :-) | {
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Some last-minute changes to beautify the Perceiver docs. | {
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https://api.github.com/repos/huggingface/transformers/issues/14785 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14785/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14785/comments | https://api.github.com/repos/huggingface/transformers/issues/14785/events | https://github.com/huggingface/transformers/issues/14785 | 1,081,235,167 | I_kwDOCUB6oc5Aclbf | 14,785 | Share custom pipelines on Huggingface Hub | {
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"cc @osanseviero and @LysandreJik!",
"Hey @fhamborg! That would be a super cool complement to @sgugger's great work on making models/tokenizers/configurations accessible from the hub!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be... | 1,639 | 1,704 | 1,645 | NONE | null | # 🚀 Feature request
Publish and share custom pipelines on Huggingface Hub.
## Motivation
It seems that the models section on Huggingface Hub is currently useful only for use cases supported out-of-the-box by the huggingface/transformers library, e.g., for sequence classification, masked pretraining, and seque... | {
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"Also tested on slow tests of:\r\n- T5\r\n- BART\r\n- GPT2\r\n- RAG",
"@Narsil it would be amazing if you could take a closer look here",
"Also cc @ydshieh for info",
"Can we also take care of the 2 hacks that were included:\r\n\r\n- remove `attention_mask` from `modeling_vit.py` and `modeling_deit.py` (this ... | 1,639 | 1,639 | 1,639 | MEMBER | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/14783 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14783/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14783/comments | https://api.github.com/repos/huggingface/transformers/issues/14783/events | https://github.com/huggingface/transformers/pull/14783 | 1,081,165,614 | PR_kwDOCUB6oc4v5Zsr | 14,783 | Update Perceiver code examples | {
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This PR:
- fixes the code examples of `PerceiverModel` and `PerceiverForMaskedLM`
- adds a link to the Perceiver blog post.
Fixes #14775 | {
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"Hi @MarkusSagen, this is an interesting issue! Our fast tokenizers are implemented in Rust, and tracing that will be impossible. However, there is usually a slower pure-Python version as well. It may be possible to trace these as a Tensorflow graph, but I've never done it myself. The tokenizers are designed for cr... | 1,639 | 1,690 | 1,641 | CONTRIBUTOR | null | # 🚀 Feature request
Currently, huggingface tokenizers support as input either a list of strings or strings. It would be great if the tokenizers could support `Tensorflow tensor of strings` or `Keras.layers.Input` as input also.
## Motivation
When working with end-to-end TensorFlow model, and especially with Tenso... | {
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"> The test asserts that betas[0] < 1.0 so it seems like the current error is correct.\r\n\r\nThanks for your reply. \r\n I mean, that there is a incorrect format of the interval indicates, as shown below:\r\n> if I initialize a AdamW optimizer with error betas' values like [0.1, 2], there would raise a ValueError ... | 1,639 | 1,640 | 1,640 | CONTRIBUTOR | null | # What does this PR do?
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"@Narsil thanks for your feedback and catching that copy-paste error! I added something to the docstring and fixed the error.\r\n\r\n@patrickvonplaten any comments?\r\n\r\n"
] | 1,639 | 1,640 | 1,640 | MEMBER | null | # What does this PR do?
This PR are continues the work and discussions from #12219 with a fresh start.
It integrates the custom `stopping_criteria` and `logits_processor` with the following logic:
- the default `stopping_criteria`/`logits_processor` are created from the arguments and model's config
- if addit... | {
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https://api.github.com/repos/huggingface/transformers/issues/14778 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14778/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14778/comments | https://api.github.com/repos/huggingface/transformers/issues/14778/events | https://github.com/huggingface/transformers/issues/14778 | 1,080,885,625 | I_kwDOCUB6oc5AbQF5 | 14,778 | Nan when training LayoutLM_V2 Model | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,639 | 1,642 | 1,642 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.13.0
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyTorch version... | {
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https://api.github.com/repos/huggingface/transformers/issues/14777 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14777/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14777/comments | https://api.github.com/repos/huggingface/transformers/issues/14777/events | https://github.com/huggingface/transformers/pull/14777 | 1,080,703,632 | PR_kwDOCUB6oc4v33t7 | 14,777 | Added forward pass of test_inference_image_classification_head | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,639 | 1,642 | 1,642 | CONTRIBUTOR | null |
# What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/14776 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14776/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14776/comments | https://api.github.com/repos/huggingface/transformers/issues/14776/events | https://github.com/huggingface/transformers/pull/14776 | 1,080,542,646 | PR_kwDOCUB6oc4v3VN_ | 14,776 | Simplify T5 docs | {
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@NielsRogge | {
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https://api.github.com/repos/huggingface/transformers/issues/14775 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14775/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14775/comments | https://api.github.com/repos/huggingface/transformers/issues/14775/events | https://github.com/huggingface/transformers/issues/14775 | 1,080,531,930 | I_kwDOCUB6oc5AZ5va | 14,775 | Errors in running Perceiver example with transformers-4.14.0.dev0 | {
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"Hi,\r\n\r\nThanks for your interest in Perceiver! The reason you're getting an error is because the `logits` that come out of the model have a sequence length of 2048, as the decoder of `PerceiverForMaskedLM` defines a sequence length of 2048 which you can see [here](https://github.com/huggingface/transformers/blo... | 1,639 | 1,639 | 1,639 | NONE | null | Python3.8, torch-1.7.1, transformers-4.14.0.dev0
Errors in running example on https://huggingface.co/docs/transformers/model_doc/perceiver
```python
from transformers import PerceiverTokenizer, PerceiverForMaskedLM
import torch
tokenizer = PerceiverTokenizer.from_pretrained('deepmind/language-perceiver')
mode... | {
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https://api.github.com/repos/huggingface/transformers/issues/14774 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14774/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14774/comments | https://api.github.com/repos/huggingface/transformers/issues/14774/events | https://github.com/huggingface/transformers/pull/14774 | 1,080,510,954 | PR_kwDOCUB6oc4v3OkA | 14,774 | Fix the doc_build_test job | {
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This PR fixes the `build_doc_test` job by installing Transformers from the branch instead of master. This then triggers a problem if we do an editable install because the `pull-request` environment of GitHub actions is read-only and a Python package. Thankfully just removing the `-e` solves t... | {
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https://api.github.com/repos/huggingface/transformers/issues/14773 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14773/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14773/comments | https://api.github.com/repos/huggingface/transformers/issues/14773/events | https://github.com/huggingface/transformers/issues/14773 | 1,080,487,550 | I_kwDOCUB6oc5AZu5- | 14,773 | Failed to import transformers.trainer | {
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"Seems like there is a problem in your docker container with the apex library, as the error actually comes when trying to do `from apex import amp`. The error will disappear if you uninstall `apex`, or fix the install if you wanted to use it.",
"solved!\r\n\r\nI made a docker like here: https://github.com/boostca... | 1,639 | 1,702 | 1,639 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: '4.13.0'
- Platform: Linux
- Python version: 3.8.12
- PyTorch version (GPU?): '1.10.0+cu113'
- I use a tens... | {
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https://api.github.com/repos/huggingface/transformers/issues/14772 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14772/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14772/comments | https://api.github.com/repos/huggingface/transformers/issues/14772/events | https://github.com/huggingface/transformers/issues/14772 | 1,080,471,834 | I_kwDOCUB6oc5AZrEa | 14,772 | A bug in T5LayerNorm | {
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"Hey @jk-jung,\r\n\r\nThe naming might be a bit off here, but assuming that the mean is 0 this is actually the correct formula ;-)"
] | 1,639 | 1,639 | 1,639 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.13.0
- Platform:
- Python version:
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Using GP... | {
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https://api.github.com/repos/huggingface/transformers/issues/14771 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14771/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14771/comments | https://api.github.com/repos/huggingface/transformers/issues/14771/events | https://github.com/huggingface/transformers/pull/14771 | 1,080,424,509 | PR_kwDOCUB6oc4v28oM | 14,771 | Update Using AWS Inferentia to run HuggingFace TorchScript model | {
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"This is a PR for updating TorchScript section with guidance on how to use AWS Inf1 instances to run HuggingFace transformer models. @philschmid, @LysandreJik I look forward to your reviews. ",
"@kct22aws could you rebase your branch with the master so only your changes are shown? An in addition the `check_code_q... | 1,639 | 1,641 | 1,641 | CONTRIBUTOR | null | # What does this PR do?
This PR appended a new section "Using HuggingFace TorchScript model in AWS Inf1 using Neuron SDK" to the TorchScript section of the HuggingFace transformer documentation.
<!--
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https://api.github.com/repos/huggingface/transformers/issues/14770 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14770/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14770/comments | https://api.github.com/repos/huggingface/transformers/issues/14770/events | https://github.com/huggingface/transformers/issues/14770 | 1,080,150,752 | I_kwDOCUB6oc5AYcrg | 14,770 | Adding new tokens to various models changes tokenization of adjacent elements in strings | {
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"## Environment\r\n* Python version: 3.6.13\r\n* Platform: Ubuntu 18.04.5 LTS\r\n* `PyTorch` version (GPU?): 1.10.1 (True)\r\n* `transformers` version: 3.3.1\r\n* Flax version (CPU?/GPU?/TPU?): not installed (NA)\r\n* Jax version: not installed\r\n* JaxLib version: not installed\r\n* Using GPU in script?: no\r\n* ... | 1,639 | 1,706 | 1,643 | NONE | null | ## Environment info
- `transformers` version: 4.13.0
- Platform: Windows-10-10.0.19043-SP0
- Python version: 3.9.7
- PyTorch version (GPU?): 1.10.0+cu113 (True)
- Tensorflow version (GPU?): 2.7.0 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not instal... | {
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https://api.github.com/repos/huggingface/transformers/issues/14769 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14769/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14769/comments | https://api.github.com/repos/huggingface/transformers/issues/14769/events | https://github.com/huggingface/transformers/pull/14769 | 1,080,019,215 | PR_kwDOCUB6oc4v1jup | 14,769 | Fix preprocess_function in run_summarization_flax.py | {
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"@patil-suraj - could you take this one? :-)"
] | 1,639 | 1,651 | 1,639 | COLLABORATOR | null | # What does this PR do?
`run_summarization_flax.py` has
https://github.com/huggingface/transformers/blob/e7ed7ffdcb66c78d3437ed4c3a63c3640f50f436/examples/flax/summarization/run_summarization_flax.py#L535-L537
Using `jnp.array` here will cause `preprocess_function` to hang forever when it is used by `datasets... | {
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https://api.github.com/repos/huggingface/transformers/issues/14768 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14768/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14768/comments | https://api.github.com/repos/huggingface/transformers/issues/14768/events | https://github.com/huggingface/transformers/issues/14768 | 1,079,917,138 | I_kwDOCUB6oc5AXjpS | 14,768 | Length penalty for beam search | {
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"Tagging @patil-suraj as it involves summarization.",
"Hi @tuvuumass , there's the `length_penalty` argument in the `generate` method, which you can use for this.\r\nhttps://huggingface.co/docs/transformers/master/en/main_classes/model#transformers.generation_tf_utils.TFGenerationMixin.generate.length_penalty",
... | 1,639 | 1,639 | 1,639 | CONTRIBUTOR | null | Hey everyone!
I want to reproduce T5's result on the CNN/DM summarization task. As described in the paper, T5 uses beam search with a beam width of 4 and a length penalty of α = 0.6 ([Wu et al., 2016](https://arxiv.org/abs/1609.08144)). However, I couldn't find a specific argument to set the length penalty α (which ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14767 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14767/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14767/comments | https://api.github.com/repos/huggingface/transformers/issues/14767/events | https://github.com/huggingface/transformers/issues/14767 | 1,079,873,616 | I_kwDOCUB6oc5AXZBQ | 14,767 | Is there a way to batch examples by max number of tokens using tokenizers and datasets? | {
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"Yes, see this answer on our forum: https://discuss.huggingface.co/t/are-dynamic-padding-and-smart-batching-in-the-library/10404/4",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease not... | 1,639 | 1,667 | 1,642 | NONE | null | I want to batch my dataset ("super_glue") by the number of tokens instead of the number of sentences. Does this library have any Sampler or Collater that can do this while using a huggingface tokenizer and a huggingface dataset? | {
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https://api.github.com/repos/huggingface/transformers/issues/14766 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14766/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14766/comments | https://api.github.com/repos/huggingface/transformers/issues/14766/events | https://github.com/huggingface/transformers/issues/14766 | 1,079,834,160 | I_kwDOCUB6oc5AXPYw | 14,766 | Nan when training LayoutLM_V2 Model | {
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<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.13.0
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyTorch version... | {
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https://api.github.com/repos/huggingface/transformers/issues/14765 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14765/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14765/comments | https://api.github.com/repos/huggingface/transformers/issues/14765/events | https://github.com/huggingface/transformers/pull/14765 | 1,079,780,548 | PR_kwDOCUB6oc4v0xXA | 14,765 | Adding documentation on how to overload `SacreBLEU` arguments | {
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"This seems like a very niche use case so let's not clutter the example README with it. We can add a comment in the actual script if we feel it's really necessary, but we already say everywhere that those examples are **just examples** and that users should customize them to their needs.",
"I am perfectly fine no... | 1,639 | 1,639 | 1,639 | CONTRIBUTOR | null | in the example
# What does this PR do?
Fixes #14758
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https://api.github.com/repos/huggingface/transformers/issues/14764 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14764/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14764/comments | https://api.github.com/repos/huggingface/transformers/issues/14764/events | https://github.com/huggingface/transformers/issues/14764 | 1,079,777,428 | I_kwDOCUB6oc5AXBiU | 14,764 | finetune_wav2vec2_xlsr_turkish.sh can not find wav | {
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"Hi @Qoboty! Sorry for the inconvenience, `common_voice` recently got upgraded to use `datasets.features.Audio` with archive streaming, so the older scripts in `research_projects/wav2vec2/` that used string audio paths no longer support it. \r\n\r\nTry running an experiment with this example, which is actively main... | 1,639 | 1,661 | 1,642 | NONE | null | Hi @patrickvonplaten
when using transformers/examples/research_projects/wav2vec2/finetune_wav2vec2_xlsr_turkish.sh
I got err:
0%| | 0/3478 [00:00<?, ?ex/s]formats: can't open input file `common_voice_tr_17346025.mp3': No such file or directory
0%| | 0/3478 [00:00<?, ?ex/s]
Traceback (most... | {
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https://api.github.com/repos/huggingface/transformers/issues/14763 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14763/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14763/comments | https://api.github.com/repos/huggingface/transformers/issues/14763/events | https://github.com/huggingface/transformers/issues/14763 | 1,079,652,527 | I_kwDOCUB6oc5AWjCv | 14,763 | Question about how to modify token embedding before sending to bert | {
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"You can do it as follows:\r\n\r\n```\r\nfrom transformers.models.bert.modeling_bert import BertPreTrainedModel , BertEmbeddings, BertEncoder, BertPooler\r\n\r\nclass CustomBertModel(BertPreTrainedModel):\r\n def __init__(self, config, add_pooling_layer=True):\r\n super().__init__(config)\r\n self.... | 1,639 | 1,639 | 1,639 | NONE | null | Anyone knows how to modify the embedding before sending to bert using transformer? Inherit the `BertPreTrainedModel`?
such as
```
# get token embedding
embedding_output = self.embeddings(
input_ids=input_ids,
position_ids=position_ids,
token_type_ids=token_t... | {
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https://api.github.com/repos/huggingface/transformers/issues/14762 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14762/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14762/comments | https://api.github.com/repos/huggingface/transformers/issues/14762/events | https://github.com/huggingface/transformers/issues/14762 | 1,079,648,389 | I_kwDOCUB6oc5AWiCF | 14,762 | make docs failing | {
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"Yes we are not using sphinx anymore to build the doc. The contributing guide will be updated in the coming days.",
"Okay\r\n"
] | 1,639 | 1,639 | 1,639 | CONTRIBUTOR | null | https://github.com/huggingface/transformers/blob/2a606f9974feb0f7578e6a638c7e5b548523ecb4/CONTRIBUTING.md?plain=1#L211-L221
```bash
make docs
cd docs && make html SPHINXOPTS="-W -j 4"
Application error:
config directory doesn't contain a conf.py file (source)
make[1]: *** [html] Error 2
make: *** [docs] Erro... | {
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https://api.github.com/repos/huggingface/transformers/issues/14761 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14761/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14761/comments | https://api.github.com/repos/huggingface/transformers/issues/14761/events | https://github.com/huggingface/transformers/issues/14761 | 1,079,551,436 | I_kwDOCUB6oc5AWKXM | 14,761 | TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType | {
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"How are you downloading the files, and what are the size of the files @pratikchhapolika ?",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [co... | 1,639 | 1,642 | 1,642 | NONE | null | I am downloading the model <<https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384/tree/main>> **microsoft/Multilingual-MiniLM-L12-H384** and then using it.
**Transformer Version: '4.11.3'**
Following are the files in the links:
<img width="277" alt="Screenshot 2021-12-14 at 3 29 09 PM" src="https://user... | {
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https://api.github.com/repos/huggingface/transformers/issues/14760 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14760/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14760/comments | https://api.github.com/repos/huggingface/transformers/issues/14760/events | https://github.com/huggingface/transformers/issues/14760 | 1,079,532,876 | I_kwDOCUB6oc5AWF1M | 14,760 | Addition of Swin Transformer for Computer Vision | {
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"Maybe of interest to @NielsRogge ",
"Hello, I would like to work on adding Swin. I will put out a PR sometime soon.\r\n",
"Hey @novice03, thanks for your effort! I believe that @FrancescoSaverioZuppichini is in the process of adding the `Mask2Former` model which depends on Swin, so he's probably working on tha... | 1,639 | 1,642 | 1,642 | CONTRIBUTOR | null | # 🌟 Addition Swin Transformer
## Model description
Swin Transformer (the name Swin stands for Shifted window) is initially described in arxiv, which capably serves as a general-purpose backbone for computer vision. It is basically a hierarchical Transformer whose representation is computed with shifted windows. Th... | {
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https://api.github.com/repos/huggingface/transformers/issues/14759 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14759/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14759/comments | https://api.github.com/repos/huggingface/transformers/issues/14759/events | https://github.com/huggingface/transformers/issues/14759 | 1,079,369,495 | I_kwDOCUB6oc5AVd8X | 14,759 | KeyError: 337 when training a hugging face model using pytorch | {
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"@patrickvonplaten any help on this, please !!",
"I think this is an issue with the ConvBERT tokenizer conversion cc @abhishekkrthakur ",
"@pratikchhapolika where does this error occur? would you mind posting the full stacktrace? ",
"@abhishekkrthakur This is the only error I get. The `KeyError: ***` keeps ch... | 1,639 | 1,659 | 1,646 | NONE | null | I am training a simple binary classification model using `Hugging face models` using `pytorch.`
Bert PyTorch HuggingFace.
Here is the code:
import transformers
from transformers import TFAutoModel, AutoTokenizer
from tokenizers import Tokenizer, models, pre_tokenizers, decoders, processors
... | {
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https://api.github.com/repos/huggingface/transformers/issues/14758 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14758/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14758/comments | https://api.github.com/repos/huggingface/transformers/issues/14758/events | https://github.com/huggingface/transformers/issues/14758 | 1,079,239,659 | I_kwDOCUB6oc5AU-Pr | 14,758 | SacreBLEU uses incorrect tokenizer for Japanese | {
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"Hi @ekoenitz,\r\n\r\nI am by no means an expert in this example.\r\nHowever, looking at it, it seems you are adding an argument to help `sacrebleu` figuring out the japanese tokenizer `--tokenizer ja-meca` right ?\r\n\r\nIf that's the case, the bleu score is actually calculated by Sacrebleu too and you would need ... | 1,639 | 1,639 | 1,639 | NONE | null | [SacreBLEU](https://github.com/mjpost/sacreBLEU) needs to be told to use a different tokenizer in order to properly evaluate Japanese text, but as far as I can tell the HuggingFace framework has no means with which to do this. I imagine other languages that need special tokenizers are affected as well, but I haven't t... | {
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https://api.github.com/repos/huggingface/transformers/issues/14757 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14757/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14757/comments | https://api.github.com/repos/huggingface/transformers/issues/14757/events | https://github.com/huggingface/transformers/pull/14757 | 1,079,177,228 | PR_kwDOCUB6oc4vyx_b | 14,757 | [doc] performance: groups of operations by compute-intensity | {
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I adapted it to be generic as it was originally written to be specific to data movements.
I think it'd make a great addition to the performance doc.
@sgugger | {
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