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https://api.github.com/repos/huggingface/transformers/issues/15060 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15060/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15060/comments | https://api.github.com/repos/huggingface/transformers/issues/15060/events | https://github.com/huggingface/transformers/issues/15060 | 1,095,690,134 | I_kwDOCUB6oc5BTueW | 15,060 | Feature request: m2m100_418M support on onnx | {
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"Gently pinging @michaelbenayoun @lewtun :)",
"Hi, should I ping them? or did you.\r\n",
"Hey @Jourdelune thanks for the feature request - I agree that M2M100 is a great model to support for ONNX :) \r\n\r\nJust so you know, exporting the model will only be the first step. In order to generate the translations ... | 1,641 | 1,649 | 1,649 | NONE | null | # 🚀 Feature request
Hi, it would be great if onnx could support the facebook M2M100 418M multilingual translation model!
## Motivation
I would like to run m2m100 with reduced translation time on cpu. For this I discovered onnx which reduces the translation time up to 3 times (perfect).So I ran this command I... | {
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"It seems that we have to change https://github.com/huggingface/transformers/blob/cc406da4debea3c2e7e93f42585339e79e18fd6b/src/transformers/models/hubert/modeling_tf_hubert.py#L231 \r\n\r\nto use a tensorflow max function instead https://www.tensorflow.org/api_docs/python/tf/math/maximum\r\n\r\n@gante , @Rocketknig... | 1,641 | 1,644 | 1,644 | 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
- Platform: Linux-5.4.144+-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/15058 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15058/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15058/comments | https://api.github.com/repos/huggingface/transformers/issues/15058/events | https://github.com/huggingface/transformers/pull/15058 | 1,095,508,784 | PR_kwDOCUB6oc4wnlH4 | 15,058 | Model summary doc page horizontal banners | {
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"cc: @AK391 "
] | 1,641 | 1,641 | 1,641 | CONTRIBUTOR | null | # What does this PR do?
Horizontally align model summary page banners
To achieve this results, there are 2 options:
1. Write html directly (as done in this PR)
OR
2. Create a specific svelte component & use it (something like `import SomeComponent.svelte` & `<SomeComponent banners={...}>`)
I think option2 is ... | {
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In `modeling_vision_text_dual_encoder.py`, this line (doc example) will fail
```
>>> loss, logits_per_image = outputs.loss, outputs.logits_per_imag
```
It should be `outputs.logits_per_image` (`CLIPOutput`)
## Who can review?
@patil-suraj | {
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"Hey @jsnfly,\r\n\r\nsorry for answering so late. Great job on identifying the problem! I left some improvements as comments in the PR. The problem is that if we remove `**kwargs_encoder` from `AutoModel.from_pretrained(...)` we loose functionality - *e.g.* if someone would pass `local_files_only=True`. \r\n\r\nCou... | 1,641 | 1,642 | 1,642 | CONTRIBUTOR | null | # What does this PR do?
Somewhat continuing https://github.com/huggingface/transformers/pull/15043 but concerning all of the encoder-decoder models:
If, like in this [example](https://github.com/huggingface/transformers/blob/f71fb5c36e739d8224419bb091b4c16531df829f/examples/pytorch/speech-recognition/README.md?plai... | {
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"Thanks for this table, it beautifully summarizes all possible cases and it should indeed work in any case. Here are my thoughts:\r\n\r\n## Single image\r\n\r\nIf you are providing a single image (or a list containing a single image) and not specifying the `return_tensors` argument/setting it to 'np', it should in ... | 1,641 | 1,674 | 1,674 | 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
- Platform: Ubuntu 16.04
- Python version: 3.9.7
- PyTorch version (GPU?): 1.10.1+cu113
- Tensorflow... | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discuss.huggingface.co) instead?\r\n\r\nThanks!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this stil... | 1,641 | 1,644 | 1,644 | NONE | null | I am combining a tokenizer from model A with apretrained model B.
I want to align special token ids.
I am able to change the token name such as <s> but I cannot change the token id number.
How can I aproach this problem? | {
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This PR makes sure the torch GPU + multi GPU LayoutLMv2/LayoutXLM tests are run on Github actions, by installing Detectron2 from source.
It also fixes a device issue. | {
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"I am unsure why the model would need an additional layer. Can't it all be treated by a proper loss function?",
"Thanks for the suggestion. After brainstorming with my team, it seems to be possible. I am closing this thread."
] | 1,641 | 1,642 | 1,642 | CONTRIBUTOR | null | # 🚀 Feature request
We need to be able to use the trainer for multilabel token classification problems.
## Motivation
Right now we create a custom model and a custom trainer class. The model has an additional layer for the second set of labels. Which makes the codebase complicated and harder to maintain. This... | {
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"You are using a legacy script with a recent version of Transformers, this is not going to work. You should use a version of Transformers compatible with that script, or use one of our maintained examples.",
"I had the same issue and solved by using an older release: `pip install transformers==v3.4.0`\r\n@atptour... | 1,641 | 1,645 | 1,645 | NONE | null | ## Environment info
- `transformers` version: 4.15.0
- Platform: Linux-4.18.0-193.19.1.el8_2.x86_64-x86_64-with-centos-8.2.2004-Core
- Python version: 3.6.13
- PyTorch version (GPU?): 1.10.1+cu102 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax v... | {
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https://api.github.com/repos/huggingface/transformers/issues/15050 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15050/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15050/comments | https://api.github.com/repos/huggingface/transformers/issues/15050/events | https://github.com/huggingface/transformers/issues/15050 | 1,095,042,279 | I_kwDOCUB6oc5BRQTn | 15,050 | Cannot fine-tune google/mobilebert-uncased using native Pytorch | {
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"Hi,\r\n\r\nFor training-related questions, please refer to the forum. See [here](https://discuss.huggingface.co/search?q=mobilebert) for all MobileBERT-related questions for instance.\r\n\r\nWe like to keep Github issues for bugs/feature requests.\r\n\r\nThank you!",
"This issue has been automatically marked as ... | 1,641 | 1,644 | 1,644 | NONE | null | ## Environment info
- `transformers` version: 4.12.5
- Platform: Linux-4.4.0-210-generic-x86_64-with-glibc2.23
- Python version: 3.9.7
- PyTorch version (GPU?): 1.10.0 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib ver... | {
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https://api.github.com/repos/huggingface/transformers/issues/15049 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15049/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15049/comments | https://api.github.com/repos/huggingface/transformers/issues/15049/events | https://github.com/huggingface/transformers/issues/15049 | 1,095,026,273 | I_kwDOCUB6oc5BRMZh | 15,049 | Inference API: Error with GPU inference | {
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"Hi!\r\n\r\nDo have an update on this issue? Thank you for all the support.\r\n\r\n@LysandreJik @patil-suraj",
"cc @Narsil ",
"Hi @nbravulapalli ,\r\n\r\nThere indeed seemed to have been an issue with that model.\r\nIt should be back up again.\r\n\r\nWe are actively tracking those issues to reduce them to a min... | 1,641 | 1,688 | 1,644 | NONE | null |
### Who can help
@LysandreJik @patil-suraj
## To reproduce
```
import requests
import json
headers = {"Authorization": f"Bearer {MY_BEARER_TOKEN}"}
API_URL = "https://api-inference.huggingface.co/models/gpt2"
data = json.dumps({"inputs": INPUT_TEXT, "parameters":{"num_return_sequences":NUM_SEQUENCES,... | {
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https://api.github.com/repos/huggingface/transformers/issues/15048 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15048/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15048/comments | https://api.github.com/repos/huggingface/transformers/issues/15048/events | https://github.com/huggingface/transformers/issues/15048 | 1,094,784,450 | I_kwDOCUB6oc5BQRXC | 15,048 | word_ids method is not available on fast tokenizers when using "prepare_for_model" | {
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"Hi,\r\n\r\nThe `prepare_for_model` is not a user-facing method, it's recommended to just call the tokenizer (as in your first code snippet). The `prepare_for_model` method does not set the `_encodings` field of `BatchEncoding` (this is only done in the `_encode_plus` and `_batch_encode_plus` methods of `tokenizati... | 1,641 | 1,644 | 1,644 | CONTRIBUTOR | null | Tokenizer: RoBERTa
```
hf_tokenizer = AutoTokenizer.from_pretrained("roberta-base")
hf_tokenizer.is_fast # = True
```
```
inputs = hf_tokenizer("This is a test")
print(inputs.word_ids())
input_ids = inputs["input_ids"]
```
Returns: `[None, 0, 1, 2, 3, None]`
```
inputs2 = hf_tokenizer.prepare_for_mode... | {
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https://api.github.com/repos/huggingface/transformers/issues/15047 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15047/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15047/comments | https://api.github.com/repos/huggingface/transformers/issues/15047/events | https://github.com/huggingface/transformers/issues/15047 | 1,094,699,306 | I_kwDOCUB6oc5BP8kq | 15,047 | [Trainer] Very different loss reported during training vs. at the end. | {
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"cc @sgugger ",
"It looks like the reported `\"train_loss\"` is averaged twice, so it's not accurate. Will fix this week.",
"I was actually wrong, and the training loss is properly computed (see #15096 that adds a test which is passing). Are you sure you are using the most recent version of Transformers?",
"I... | 1,641 | 1,646 | 1,646 | NONE | null | I have trained GPT from scratch. During training, I got logs outputting evaluation and 'loss', like shown below:
`{'loss': 6.5349, 'learning_rate': 0.00014698625308424393, 'epoch': 42.65}`
But after the last step I get this log, different to the previous ones:
`{'train_runtime': 751.251, 'train_samples_per_sec... | {
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https://api.github.com/repos/huggingface/transformers/issues/15046 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15046/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15046/comments | https://api.github.com/repos/huggingface/transformers/issues/15046/events | https://github.com/huggingface/transformers/pull/15046 | 1,094,611,196 | PR_kwDOCUB6oc4wktO5 | 15,046 | Adding support for `microphone` streaming within pipeline. | {
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"Hey @Narsil,\r\n\r\nI think the PR broke some slow tests:\r\n\r\n```\r\nFAILED tests/test_pipelines_automatic_speech_recognition.py::AutomaticSpeechRecognitionPipelineTests::test_speech_to_text_leveraged\r\nFAILED tests/test_pipelines_automatic_speech_recognition.py::AutomaticSpeechRecognitionPipelineTests::test_t... | 1,641 | 1,644 | 1,643 | CONTRIBUTOR | null | - Uses `ffmpeg` to get microphone data.
- Makes sure alignment is made to `size_of_sample`.
- Works by sending `{"raw": ..data.., "stride": (n, left, right),
"partial": bool, "sampling_rate": sampling_rate}`
directly to the pipeline enabling to stream partial results and still
get inference.
- Let's `partial` inf... | {
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https://api.github.com/repos/huggingface/transformers/issues/15045 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15045/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15045/comments | https://api.github.com/repos/huggingface/transformers/issues/15045/events | https://github.com/huggingface/transformers/issues/15045 | 1,094,512,401 | I_kwDOCUB6oc5BPO8R | 15,045 | [FX] `symbolic_trace` yields a TraceError for `BertModel` | {
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"Hi,\r\n\r\nIn order to symbolic trace a model, you also need to provide the input_names:\r\n\r\n```\r\nfrom transformers import BertModel\r\nfrom transformers.utils.fx import symbolic_trace\r\n\r\nmodel = BertModel.from_pretrained(\"bert-base-uncased\")\r\n\r\ntraced_model = symbolic_trace(\r\n model,\r\n in... | 1,641 | 1,641 | 1,641 | COLLABORATOR | 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: 4.16.0.dev0
- Platform: Linux
- Python version: 3.9.2
- PyTorch version (GPU?): 1.10.1+cpu
- Tensorflow ver... | {
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https://api.github.com/repos/huggingface/transformers/issues/15044 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15044/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15044/comments | https://api.github.com/repos/huggingface/transformers/issues/15044/events | https://github.com/huggingface/transformers/pull/15044 | 1,094,495,590 | PR_kwDOCUB6oc4wkVEw | 15,044 | [Fix doc examples] missing from_pretrained | {
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In a docstring,
```
model = SegformerModel("nvidia/segformer-b0-finetuned-ade-512-512")
```
fails -> should use `from_pretrained`.
This PR fixes it.
## Who can review?
@NielsRogge | {
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https://api.github.com/repos/huggingface/transformers/issues/15043 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15043/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15043/comments | https://api.github.com/repos/huggingface/transformers/issues/15043/events | https://github.com/huggingface/transformers/pull/15043 | 1,094,475,068 | PR_kwDOCUB6oc4wkQ1Q | 15,043 | [SpeechEncoderDecoder] Fix from pretrained | {
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"The other two `VisionEncoderDecoderModel` and `EncoderDecoderModel` were correct"
] | 1,641 | 1,641 | 1,641 | MEMBER | null | # 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.
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https://api.github.com/repos/huggingface/transformers/issues/15042 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15042/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15042/comments | https://api.github.com/repos/huggingface/transformers/issues/15042/events | https://github.com/huggingface/transformers/pull/15042 | 1,094,371,106 | PR_kwDOCUB6oc4wj7Ec | 15,042 | [CLIP] Fix TF test | {
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Fixes the slow TFCLIP tests by using the TF checkpoint instead of converting from `PT`. | {
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<!--
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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.
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https://api.github.com/repos/huggingface/transformers/issues/15040 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15040/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15040/comments | https://api.github.com/repos/huggingface/transformers/issues/15040/events | https://github.com/huggingface/transformers/pull/15040 | 1,094,254,191 | PR_kwDOCUB6oc4wjipd | 15,040 | [Wav2Vec2ProcessorWithLM] improve decoder download | {
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"Not super urgent the PR - would be good to be merged by early/mid next week.",
"Just released version v0.4.0 for `huggingface_hub` - reran the test suite, everything passes. \r\n\r\nMerging!"
] | 1,641 | 1,641 | 1,641 | MEMBER | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/15039 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15039/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15039/comments | https://api.github.com/repos/huggingface/transformers/issues/15039/events | https://github.com/huggingface/transformers/issues/15039 | 1,094,053,489 | I_kwDOCUB6oc5BNe5x | 15,039 | Wav2Vec2 bart-large - finetuning failing with ValueError: tokenizer has to be of type....but is <class 'transformers.models.bart.tokenization_bart_fast.BartTokenizerFast' | {
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"Hey @programmeddeath1,\r\n\r\nSorry to answer so late. Could you please provide a short code snippet that reproduces the error? Thanks!",
"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\nPlea... | 1,641 | 1,645 | 1,645 | NONE | null | Hii,
I am trying to understand how to finetune wav2vec2 models with my own decoder, I am trying to replicate the finetuning for the
patrickvonplaten/wav2vec2-2-bart-large model with the run script from
https://github.com/huggingface/transformers/tree/master/examples/pytorch/speech-recognition
The create_model... | {
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https://api.github.com/repos/huggingface/transformers/issues/15038 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15038/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15038/comments | https://api.github.com/repos/huggingface/transformers/issues/15038/events | https://github.com/huggingface/transformers/issues/15038 | 1,094,045,121 | I_kwDOCUB6oc5BNc3B | 15,038 | BERT model from pipeline hangs with multiprocessing pool | {
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"similar issue: [https://github.com/huggingface/transformers/issues/14919](url)",
"The error seems to come from Tensorflow itself, here is an example without using `pipeline` whatsoever.\r\n\r\n```python\r\nimport multiprocessing\r\nimport os\r\nfrom transformers import DistilBertTokenizer, TFDistilBertForQuestio... | 1,641 | 1,641 | 1,641 | 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==4.9.1
- Platform: macOS Catalina 10.15.7 (19H2)
- Python version: 3.7.5
- PyTorch version (GPU... | {
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https://api.github.com/repos/huggingface/transformers/issues/15037 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15037/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15037/comments | https://api.github.com/repos/huggingface/transformers/issues/15037/events | https://github.com/huggingface/transformers/pull/15037 | 1,093,906,085 | PR_kwDOCUB6oc4wibPm | 15,037 | Wrap Roberta integration test forward passes with torch.no_grad() | {
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This PR wraps forward passes in Roberta integration tests with torch.no_grad(). See issue #14642
Fixes #14642
[Issue link](https://github.com/huggingface/transformers/issues/14642)
## 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/15036 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15036/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15036/comments | https://api.github.com/repos/huggingface/transformers/issues/15036/events | https://github.com/huggingface/transformers/pull/15036 | 1,093,864,755 | PR_kwDOCUB6oc4wiS1O | 15,036 | use block_size instead of max_seq_length in tf run_clm example | {
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https://api.github.com/repos/huggingface/transformers/issues/15035 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15035/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15035/comments | https://api.github.com/repos/huggingface/transformers/issues/15035/events | https://github.com/huggingface/transformers/issues/15035 | 1,093,783,334 | I_kwDOCUB6oc5BMc8m | 15,035 | Issue with `stas/tiny-wmt19-en-de` model | {
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"Hi, tingofurro\r\n\r\nHave a look at what the model card says:\r\n\r\n> This is a tiny model that is used in the transformers test suite. It doesn't do anything useful, other than testing that modeling_fsmt.py is functional.\r\n> \r\n> Do not try to use it for anything that requires quality.\r\n\r\nThus closing th... | 1,641 | 1,641 | 1,641 | NONE | null | ## Environment info
The environment in the Hosted inference API
### Who can help
@stas00
Models:
`stas/tiny-wmt19-en-de` (I assume the issue might be there with other language pairs)
## Information
I am unable to use the model to generate translations, it seems to be generating gibberish (see Scree... | {
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https://api.github.com/repos/huggingface/transformers/issues/15034 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15034/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15034/comments | https://api.github.com/repos/huggingface/transformers/issues/15034/events | https://github.com/huggingface/transformers/issues/15034 | 1,093,697,694 | I_kwDOCUB6oc5BMICe | 15,034 | ValueError: Layer weight shape (30522, 768) not compatible with provided weight shape torch.Size([1, 15, 3072]) | {
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"Hi @mathshangw, is there a way for you to share more? We don't have knowledge of most of the variables you're showing here.",
"Hi @mathshangw! Thank you for sharing your issue with us.\r\n\r\nI see two potential issues, given the information you gave us so far:\r\n1. the `inputs2` variable in your initial script... | 1,641 | 1,644 | 1,644 | NONE | null | I tried to use word embedding from using BERT as an embedding layer using Keras like that
```
inputs2 = Input(shape=(max_length,))
sent = Embedding(vocab_size, 768, mask_zero=True)(inputs2)
model.layers[1].set_weights([embedding_matrix])
model.layers[1].trainable = False
```
but got the fo... | {
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https://api.github.com/repos/huggingface/transformers/issues/15033 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15033/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15033/comments | https://api.github.com/repos/huggingface/transformers/issues/15033/events | https://github.com/huggingface/transformers/pull/15033 | 1,093,515,272 | PR_kwDOCUB6oc4whJSQ | 15,033 | Fix doc example: mask_time_indices (numpy) has no attribute 'to' | {
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"Thank you!"
] | 1,641 | 1,651 | 1,641 | COLLABORATOR | null | # What does this PR do?
In speech to text models, there are doc examples
```
>>> mask_time_indices = _compute_mask_indices((batch_size, sequence_length), mask_prob=0.2, mask_length=2)
>>> with torch.no_grad():
... outputs = model(input_values, mask_time_indices=mask_time_indices)
```
which gi... | {
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https://api.github.com/repos/huggingface/transformers/issues/15032 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15032/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15032/comments | https://api.github.com/repos/huggingface/transformers/issues/15032/events | https://github.com/huggingface/transformers/issues/15032 | 1,093,494,323 | I_kwDOCUB6oc5BLWYz | 15,032 | Removing tokens from the tokenizer | {
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"@snoop2head , I will answer your question purely \"technically\" because in general it can be quite complicated to remove tokens from a tokenizer that has been trained with a certain algorithm. \r\n\r\nIndeed, it can seems a bit complicated to modify a tokenizer fast because they wrap the [tokenizers](https://hugg... | 1,641 | 1,675 | 1,644 | NONE | null | Any methods that I can remove unwanted tokens from the tokenizer?
Referring to #4827 , I tried to remove tokens from the tokenizer with the following code.
First, I fetch the tokenizer from huggingface hub.
```python
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_p... | {
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https://api.github.com/repos/huggingface/transformers/issues/15031 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15031/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15031/comments | https://api.github.com/repos/huggingface/transformers/issues/15031/events | https://github.com/huggingface/transformers/pull/15031 | 1,093,413,865 | PR_kwDOCUB6oc4wg0UV | 15,031 | [DocTests Speech] Add doc tests for all speech models | {
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https://api.github.com/repos/huggingface/transformers/issues/15030 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15030/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15030/comments | https://api.github.com/repos/huggingface/transformers/issues/15030/events | https://github.com/huggingface/transformers/pull/15030 | 1,093,174,654 | PR_kwDOCUB6oc4wgCna | 15,030 | Enabling `TF` on `image-classification` pipeline. | {
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<!--
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https://api.github.com/repos/huggingface/transformers/issues/15029 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15029/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15029/comments | https://api.github.com/repos/huggingface/transformers/issues/15029/events | https://github.com/huggingface/transformers/pull/15029 | 1,093,146,830 | PR_kwDOCUB6oc4wf846 | 15,029 | Hotfix `chunk_length_s` instead of `_ms`. | {
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"Feel free to merge as soon as the tests are passing :-)"
] | 1,641 | 1,641 | 1,641 | CONTRIBUTOR | null | And fixes issue that the filled in token was the padded_token which could lead to incorrect decoding.
Using the same token for CTC is better (prevent extra repetition)
# 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)... | 1,641 | 1,644 | 1,644 | CONTRIBUTOR | null | # What does this PR do?
Added a new test that tests the offsets returned by the fast tokenizers when the input is already pre-tokenized for the roberta tokenizer. To pass this test use the new version of the library tokenizers v0.11.0 (thanks to [this PR](https://github.com/huggingface/tokenizers/pull/844)).
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https://api.github.com/repos/huggingface/transformers/issues/15027 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15027/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15027/comments | https://api.github.com/repos/huggingface/transformers/issues/15027/events | https://github.com/huggingface/transformers/pull/15027 | 1,093,131,939 | PR_kwDOCUB6oc4wf52i | 15,027 | Adding QoL for `batch_size` arg (like others enabled everywhere). | {
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"Gentle reminder to fill the description of PRs pretty please, before merging @Narsil :-)",
"@sgugger Oups, sorry ! Done. :D"
] | 1,641 | 1,641 | 1,641 | CONTRIBUTOR | null | # What does this PR do?
Adds a `pipeline(.. batch_size=16)` argument.
Previously this was `__call__` only argument: `pipe = pipeline(....); pipe(..., batch_size=16)`.
This PR made both supported (like all other pipeline arguments).
Some linked issues: https://github.com/huggingface/transformers/issues/14327
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https://api.github.com/repos/huggingface/transformers/issues/15026 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15026/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15026/comments | https://api.github.com/repos/huggingface/transformers/issues/15026/events | https://github.com/huggingface/transformers/issues/15026 | 1,093,029,730 | I_kwDOCUB6oc5BJk9i | 15,026 | [Benchmark] HF Trainer on A100 | {
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"# precision: fp16 vs bf16 vs tf32 vs fp32\r\n\r\nMain interest: benchmarking the new --bf16 and --tf32 on Ampere/RTX-3090, comparatively to fp16 and fp32 modes.\r\n\r\n- bf16 is `autocast(dtype=torch.bfloat16)`\r\n- tf32 is `torch.backends.cuda.matmul.allow_tf32 = True`\r\n\r\n\r\n\r\n## Benchmark\r\n\r\nThe bench... | 1,641 | 1,648 | null | CONTRIBUTOR | null | # 🖥 Benchmarking `transformers` w/ HF Trainer on a single A100 40GB
We are going to use a special benchmarking tool that will do all the work for us. https://github.com/huggingface/transformers/pull/14934
This is the index post and specific benchmarks are in their own posts below:
1. [fp16 vs bf16 vs tf32 vs ... | {
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https://api.github.com/repos/huggingface/transformers/issues/15025 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15025/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15025/comments | https://api.github.com/repos/huggingface/transformers/issues/15025/events | https://github.com/huggingface/transformers/issues/15025 | 1,093,027,454 | I_kwDOCUB6oc5BJkZ- | 15,025 | Which model checkpoint should be selected for evaluation? | {
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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)... | 1,641 | 1,644 | 1,644 | NONE | null | According to this sample:
https://github.com/huggingface/transformers/blob/master/examples/pytorch/summarization/run_summarization.py
I get many checkpoints.

Which should be selected for testing | {
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https://api.github.com/repos/huggingface/transformers/issues/15024 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15024/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15024/comments | https://api.github.com/repos/huggingface/transformers/issues/15024/events | https://github.com/huggingface/transformers/issues/15024 | 1,093,024,646 | I_kwDOCUB6oc5BJjuG | 15,024 | Training causal language models from scratch without grouping independent data samples into blocks | {
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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)... | 1,641 | 1,644 | 1,644 | NONE | null | Trying to train a causal language model from scratch in Pytorch using run_clm_no_trainer script.
My dataset has independent sentences separated by newlines.
The current script groups these sentence (which are image captions) while training which creates erroneous results when sampling for generation
Currently I'm t... | {
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https://api.github.com/repos/huggingface/transformers/issues/15023 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15023/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15023/comments | https://api.github.com/repos/huggingface/transformers/issues/15023/events | https://github.com/huggingface/transformers/pull/15023 | 1,093,003,748 | PR_kwDOCUB6oc4wffi5 | 15,023 | [doc] normalize HF Transformers string | {
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That was a tricky one with UTF32 emoji. This worked.
```
LC_ALL=C find . -type d -name ".git" -prune -o -type f -exec perl -pi -e 's|(\xF0\x9F\xA4\x97 Transformer) |$1s |' {} \;
```
To grep I had to do:
```
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https://api.github.com/repos/huggingface/transformers/issues/15022 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15022/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15022/comments | https://api.github.com/repos/huggingface/transformers/issues/15022/events | https://github.com/huggingface/transformers/pull/15022 | 1,092,997,378 | PR_kwDOCUB6oc4wfeNR | 15,022 | Enable AMP for xla:gpu device in trainer class | {
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"Oh, interesting! Thanks for your contribution, pinging @sgugger on the issue.",
"> I'm not entirely sure about this PR in the sense that PyTorch XLA support is mainly for TPU, and I don't know if traditional mixed precision training with the gradient scaler will work on TPUs.\r\n> \r\n> So we should probably spl... | 1,641 | 1,642 | 1,642 | CONTRIBUTOR | null | # What does this PR do?
This PR enables AMP in trainer class for xla:gpu device.
# Discussion
It looks like the torch_xla support in trainer class is primarily for xla:tpu device.
I found the following features may be useful but not essential and I can include them in this PR if necessary:
1. Rename `tpu` to `x... | {
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https://api.github.com/repos/huggingface/transformers/issues/15021 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15021/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15021/comments | https://api.github.com/repos/huggingface/transformers/issues/15021/events | https://github.com/huggingface/transformers/issues/15021 | 1,092,950,686 | I_kwDOCUB6oc5BJRqe | 15,021 | AutoTokenizer unable to load pre-trained bert-base-uncased tokenizer | {
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"do you have a folder named `bert-large-uncased` where you're running this code?",
"OMG! I just realized there's a file I downloaded long ago in this directory that's named `bert-base-uncased` wow is this embarrassing! "
] | 1,641 | 1,641 | 1,641 | NONE | null | Hello! I am running the following code to load the bert-base-uncased tokenizer:
```py
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
```
which results in the following error:
```
-------------------------------------------------------------------------... | {
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https://api.github.com/repos/huggingface/transformers/issues/15020 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15020/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15020/comments | https://api.github.com/repos/huggingface/transformers/issues/15020/events | https://github.com/huggingface/transformers/issues/15020 | 1,092,886,518 | I_kwDOCUB6oc5BJB_2 | 15,020 | [Trainer] finetuning: larger batch-size leading to a worse train loss | {
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"OK, the issue was that my benchmark is very short and with less steps to take when the batches are larger, the model simply doesn't have a chance to step down far enough.\r\n\r\nSo such changes will require raising lr, but more realistically to increase the dataset size, since one can't make LR bigger proportional... | 1,641 | 1,641 | 1,641 | CONTRIBUTOR | null | I was just running a [benchmark to compare the speed up of enabling various `--gradient_accumulation_steps` levels](https://github.com/huggingface/transformers/issues/14608#issuecomment-1004392537) and I have noticed that the lm loss gets progressively worse and by much with enlarging of `gradient_accumulation_steps`:
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https://api.github.com/repos/huggingface/transformers/issues/15019 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15019/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15019/comments | https://api.github.com/repos/huggingface/transformers/issues/15019/events | https://github.com/huggingface/transformers/pull/15019 | 1,092,872,341 | PR_kwDOCUB6oc4wfFIP | 15,019 | Make OpenAIGPTTokenizer work with SpaCy 2.x and 3.x | {
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"I'm not able to test the changes locally. When I run `pip install -e \".[dev]\"`, I encounter a build error and the install fails. It doesn't look like pytest coverage is sufficient here either since SpaCy and ftfy are not required by transformers, and the code can execute correctly without them being installed.",... | 1,641 | 1,641 | 1,641 | CONTRIBUTOR | null | SpaCy 3.x introduced an API change to creating the tokenizer that
breaks OpenAIGPTTokenizer. The old API for creating the tokenizer in
SpaCy 2.x no longer works under SpaCy 3.x, but the new API for creating
the tokenizer in SpaCy 3.x DOES work under SpaCy 2.x. Switching to the
new API should allow OpenAIGPTTokenize... | {
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"updated.",
"@stas00 This can be merged !"
] | 1,641 | 1,641 | 1,641 | CONTRIBUTOR | null | - I found some mistakes and fixed them. sorry @stas00
- In addition, `DataParallel` and `DistributedDataParallel` are marked as code because they are class names. (I was trying to switch DataParallel to DataParallelism, but I realized that this means name of class)
## Reviewers
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] | 1,641 | 1,643 | 1,643 | MEMBER | null | # What does this PR do?
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"Thank you!"
] | 1,641 | 1,651 | 1,641 | COLLABORATOR | null | # What does this PR do?
A one line fix for doc example in `modeling_wav2vec2.py`
## Who can review?
@patrickvonplaten | {
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# What does this PR do?
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"updated. @stas00 "
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- Small changes.
## Reviewers
@stas00 | {
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"Hi,\r\n\r\nCurrently the feature extractors only accept a list of individual PyTorch tensors/Numpy arrays/PIL images in case you want to preprocess a batch of images. One cannot provide a batch of images as a single PyTorch tensor to the feature extractor. \r\n\r\nHowever, there's a feature request to add this (se... | 1,641 | 1,655 | 1,644 | 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
- Platform: macOS
- Python version: 3.8
- PyTorch version (GPU?): CPU
- Tensorflow version (GPU?):
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"Oh wow that's quite a big change! Also cc @patrickvonplaten ",
"Thanks for the change @ydshieh - I'm quite sure that most of the docstring tests in the mentioned files fail at the moment. Could you maybe do those changes: https://github.com/huggingface/transformers/pull/15031/files#r778215725 in your PR as well ... | 1,641 | 1,651 | 1,643 | COLLABORATOR | null | # What does this PR do?
As discussed in a previous email, I updated the file `utils/documentation_tests.txt`:
- change the current 2 `.rst` files to the new `.mdx` files
- add the pytorch modeling files that have no example issue (I tested them locally)
There are still some modeling files containing example... | {
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"How long does this check take for large files?",
"@LysandreJik on my modest box (i7-4790, old sdd) it takes 800ms for 300Mo, which is on Par with the load time.\r\n\r\nThis only happens on failure too not when it works.",
"Sorry, coming back to this now.\r\n\r\nIf this only happens on failure then I think it's... | 1,641 | 1,663 | 1,663 | CONTRIBUTOR | null | # What does this PR do?
Fixes #14603
When an error is triggered when loading weights, before finally
crashing, attempt to check disk corruption by actually checking the
SHA signature of files.
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Backward compatibility broken in
https://github.com/huggingface/transformers/pull/14988
This restabilishes the correct outputs.
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https://api.github.com/repos/huggingface/transformers/issues/15006 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15006/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15006/comments | https://api.github.com/repos/huggingface/transformers/issues/15006/events | https://github.com/huggingface/transformers/issues/15006 | 1,092,292,389 | I_kwDOCUB6oc5BGw8l | 15,006 | "total_flos" showing much bigger number than expected | {
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"cc @TevenLeScao since he implemented the feature.",
"Hey, sorry for the incorrect number - this function was originally written for language models, and might not transfer to vision models, for example. Do you need this number or is it just for checking?",
"Hello, I was trying to benchmark my A100 server, so h... | 1,641 | 1,702 | 1,644 | 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: 4.14.1
- Platform: Ubuntu 20.04.1
- Python version: 3.8.5
- PyTorch version (GPU?): 1.8.0 (True)
- Tensorfl... | {
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https://api.github.com/repos/huggingface/transformers/issues/15005 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15005/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15005/comments | https://api.github.com/repos/huggingface/transformers/issues/15005/events | https://github.com/huggingface/transformers/pull/15005 | 1,092,051,498 | PR_kwDOCUB6oc4wca6P | 15,005 | Add Flax RoFormer | {
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"Waiting for the CI to be green and then we can merge",
"Merging - thanks a lot for adding this model @stancld !"
] | 1,641 | 1,641 | 1,641 | CONTRIBUTOR | null | # What does this PR do?
This PR adds the flax implementation of `RoFormer` model.
Fixes #14605
## Before submitting
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [x] W... | {
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https://api.github.com/repos/huggingface/transformers/issues/15004 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15004/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15004/comments | https://api.github.com/repos/huggingface/transformers/issues/15004/events | https://github.com/huggingface/transformers/issues/15004 | 1,092,040,164 | I_kwDOCUB6oc5BFzXk | 15,004 | How to define the self-attention layer with transformers | {
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"Hey @193769981, `BertLayer` is defined here:\r\n\r\nhttps://github.com/huggingface/transformers/blob/e68c3756fea7c811d02b8470539ae17ec3ec0e71/src/transformers/models/bert/modeling_bert.py#L445\r\n\r\n`RobertaLayer` is a copy of `BertLayer`, so the two should be identical. \r\n\r\nhttps://github.com/huggingface/tra... | 1,641 | 1,641 | 1,641 | NONE | null | I want to use 'BertLayer'or 'RobertaLayer' to define a self-attention layer,but I can't find the definition of 'RobertaLayer'.Can you provide some relevant documents?Is this API cancelled? Thanks!
“”“
self.basicblocks = nn.ModuleList()
self.n_layers = 3
trans_heads = 8
trans_drop = 0.1
... | {
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https://api.github.com/repos/huggingface/transformers/issues/15003 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15003/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15003/comments | https://api.github.com/repos/huggingface/transformers/issues/15003/events | https://github.com/huggingface/transformers/issues/15003 | 1,092,026,259 | I_kwDOCUB6oc5BFv-T | 15,003 | AlbertTokenizer doesn't decode special tokens properly | {
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"Update: there are many more SentencePiece tokenizers that may require an update, see #11716",
"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 [... | 1,641 | 1,677 | 1,677 | CONTRIBUTOR | null | Related to #5142, `AlbertTokenizer` (which uses SentencePiece) doesn't decode special tokens (like [CLS], [MASK]) properly. This issue was discovered when adding the Nystromformer model (#14659), which uses this tokenizer.
To reproduce (Transformers v4.15 or below):
```
!pip install -q transformers sentencepiece... | {
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https://api.github.com/repos/huggingface/transformers/issues/15002 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15002/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15002/comments | https://api.github.com/repos/huggingface/transformers/issues/15002/events | https://github.com/huggingface/transformers/pull/15002 | 1,091,894,067 | PR_kwDOCUB6oc4wb993 | 15,002 | Fix a little typo | {
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"Thank you"
] | 1,641 | 1,641 | 1,641 | CONTRIBUTOR | 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/15001 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15001/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15001/comments | https://api.github.com/repos/huggingface/transformers/issues/15001/events | https://github.com/huggingface/transformers/pull/15001 | 1,091,842,158 | PR_kwDOCUB6oc4wbzuy | 15,001 | Fix TFEncoderDecoder labels handling #14357 | {
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Fixes #14357
## Who can review?
@Rocketknight1 | {
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https://api.github.com/repos/huggingface/transformers/issues/15000 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/15000/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/15000/comments | https://api.github.com/repos/huggingface/transformers/issues/15000/events | https://github.com/huggingface/transformers/pull/15000 | 1,091,793,663 | PR_kwDOCUB6oc4wbqEt | 15,000 | Fixing QA when `sequence_ids` is None (instead of 0, 1). | {
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"This is incorrect actually"
] | 1,641 | 1,641 | 1,641 | CONTRIBUTOR | null | # What does this PR do?
Attempts to fix flaky test (and bug).
`tokenizer.sequence_ids(span)` was returning [None, 0, 0, 0, None, 1, 1, 1,1 , None]
and the test to make the mask for answers in question-answering is
[tok != 1 if question_first else 0].
1 and 0 are both != None so all special tokens would be included ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14999 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14999/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14999/comments | https://api.github.com/repos/huggingface/transformers/issues/14999/events | https://github.com/huggingface/transformers/pull/14999 | 1,091,674,137 | PR_kwDOCUB6oc4wbRWu | 14,999 | fix model table cell text alignment | {
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The current new model table in [index.mdx](https://github.com/ydshieh/transformers/blob/master/docs/source/index.mdx) left align table cell texts. This PR makes them center-aligned.
On master:
? | {
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"Not sure why you don't want to leverage batching, because it's always faster than passing each sentence at a time through the model:\r\n\r\n```\r\nfrom transformers import AutoTokenizer, AutoModelForSeq2SeqLM\r\nimport torch\r\n\r\ndevice = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\r\n\r\nto... | 1,640 | 1,644 | 1,644 | NONE | null | I am using a Marian Model for translating from English to Arabic. I want to use this translation per sentence (no batching).
I am using this simple code:
```
en_ar_tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ar")
en_ar_model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-... | {
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"Hey @lonngxiang, can you double check your transformers package version? I'm unable to reproduce on a fresh [Colab notebook](https://colab.research.google.com/drive/1-FUJSSFAl88foTbyqGHyFtwgvHMXTyBV?usp=sharing).",
"This issue has been automatically marked as stale because it has not had recent activity. If you ... | 1,640 | 1,644 | 1,644 | NONE | null | transformers 4.12.5
from transformers import AutoModelForTokenClassification,AutoTokenizer,pipeline
model = AutoModelForTokenClassification.from_pretrained('uer/roberta-base-finetuned-cluener2020-chinese')
tokenizer = AutoTokenizer.from_pretrained('uer/roberta-base-finetuned-cluener2020-chinese')
ner =... | {
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To add a new benchmark entry post it in an Issue (separately or as a comment in an existing issue) and then link from here. If you have edit rights please add a link directly to this post, otherwise please ... | {
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"Hello @catqaq, \r\n\r\nRegarding the fact that `tokenizer.tokenize(\"happy↖\")` outputs `['[UNK]']`, this behavior is specific to the **WordPiece** Tokenization algorithm, which is the algorithm used by `BertTokenizer`. If you want to find out more, I refer you to our course dealing exactly with these concepts ([c... | 1,640 | 1,646 | 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: 4.2.1
- Platform: Linux-3.10.0-957.el7.x86_64-x86_64-with-debian-buster-sid
- Python version: 3.6.13
- PyTor... | {
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https://api.github.com/repos/huggingface/transformers/issues/14994 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14994/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14994/comments | https://api.github.com/repos/huggingface/transformers/issues/14994/events | https://github.com/huggingface/transformers/pull/14994 | 1,091,315,286 | PR_kwDOCUB6oc4waIQS | 14,994 | Allow training to resume even if RNG states are not properly loaded | {
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This PR allows training to resume even if the loading of the RNG state fail in multi-GPU DataParallel mode because less GPUs are used than during the original training.
Fixes #14554 | {
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https://api.github.com/repos/huggingface/transformers/issues/14993 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14993/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14993/comments | https://api.github.com/repos/huggingface/transformers/issues/14993/events | https://github.com/huggingface/transformers/issues/14993 | 1,091,313,978 | I_kwDOCUB6oc5BDCE6 | 14,993 | Unexpected usage of `next_token_scores` and `beam_scores` in `beam_sample()` | {
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"Hey @jmzhao,\r\n\r\nThanks for the in-detail description. What you are saying is correct and we have chose to stick to this algorithm simply because that's how we implemented it the first time and we didn't want to break backwards compatibility anymore afterwards. The problem with `beam_sample()` IMO is that there... | 1,640 | 1,644 | 1,644 | 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: 4.9.2
- Platform: Linux
- Python version: 3.8.10
- PyTorch version (GPU?): 1.9.0+cu111 (True)
- Tensorflow ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14992 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14992/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14992/comments | https://api.github.com/repos/huggingface/transformers/issues/14992/events | https://github.com/huggingface/transformers/pull/14992 | 1,091,311,034 | PR_kwDOCUB6oc4waHX8 | 14,992 | Add model like | {
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"This is really cool, looking forward to it!",
"Once you're happy with it, we can then put it to practical use and give it a good real case test by re-doing https://github.com/huggingface/transformers/pull/14084 which got out of sync with all the recent revamps.\r\n\r\nSo basically cloning `GPT2` to create `GPT... | 1,640 | 1,643 | 1,643 | COLLABORATOR | null | # What does this PR do?
This PR adds a new command `transformers-cli add-new-model-like` that creates a new model in the Transformers library exactly like an existing one, for models we want to add that are just tweaked versions of an existing model.
Fixes #14032
Note that this PR is still a draft, I'm just pu... | {
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https://api.github.com/repos/huggingface/transformers/issues/14991 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14991/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14991/comments | https://api.github.com/repos/huggingface/transformers/issues/14991/events | https://github.com/huggingface/transformers/pull/14991 | 1,091,195,131 | PR_kwDOCUB6oc4wZvlk | 14,991 | Fix saving FlaubertTokenizer configs | {
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class (XLMTokenizer) in order to be saved. This was not the case for
do_lowercase config. Thus it was not saved by save_pretrained() method
and saving and reloading the tokenizer changed its behaviour.
This commit fixes it.
# What does this PR... | {
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https://api.github.com/repos/huggingface/transformers/issues/14990 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14990/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14990/comments | https://api.github.com/repos/huggingface/transformers/issues/14990/events | https://github.com/huggingface/transformers/issues/14990 | 1,091,120,790 | I_kwDOCUB6oc5BCS6W | 14,990 | When using bert-base-chinese model, except for the first one, other uppercase English letters that are the same in succession will be ignored. And the input_id of different uppercase English characters is the same | {
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"hi!\r\n@vanpelt @pvl @arfon @xeb \r\ncan someone hele me? \r\nthank you all very much.",
"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 [cont... | 1,640 | 1,644 | 1,644 | 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: **4.12.3**
- Platform: **macos**
- Python version: 1.7.0
- PyTorch version (GPU?):No
- Tensorflow version (... | {
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https://api.github.com/repos/huggingface/transformers/issues/14989 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14989/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14989/comments | https://api.github.com/repos/huggingface/transformers/issues/14989/events | https://github.com/huggingface/transformers/issues/14989 | 1,091,070,983 | I_kwDOCUB6oc5BCGwH | 14,989 | EncoderDecoderModel loss decreased unbelievably and the generated text were repetitive 4.12.0 | {
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"Hey @zzhongzz,\r\n\r\nThanks for the issue! Sorry this will be quite difficult to debug from my side as I would have to guess what the difference might be. Could you try to find an **easy to reproduce** difference between 4.11.3 and 4.12.0? E.g. something like\r\n\r\n```python\r\ndummy_inputs = # some input_ids\r\... | 1,640 | 1,646 | 1,646 | NONE | null | Hi,
I am training an EncoderDecoderModel with BertGenerationEncoder and BertGenerationDecoder from scratch (no pretrain) on a custom dataset with about 10k sequences. I found that the loss decreased unbelievably fast to a level which I thought was impossible for seq2seq task. And the generated texts were just repeti... | {
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https://api.github.com/repos/huggingface/transformers/issues/14988 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14988/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14988/comments | https://api.github.com/repos/huggingface/transformers/issues/14988/events | https://github.com/huggingface/transformers/pull/14988 | 1,091,016,023 | PR_kwDOCUB6oc4wZJ6y | 14,988 | Adding `num_return_sequences` support for text2text generation. | {
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# What does this PR do?
Superseed https://github.com/huggingface/transformers/pull/14411 and adds support
for multiple returned sequences from generate in t2t pipeline.
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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)... | 1,640 | 1,644 | 1,644 | NONE | null | when I run under the debug mode, the length of dataset is 500, but the length of prediction is 498, I can't find the causes.... | {
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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)... | 1,640 | 1,646 | 1,646 | NONE | null | In the train_config.json file, I set:
"model_name_or_path": "ckiplab/albert-tiny-chinese",
"tokenizer_name": "bert-base-chinese",
this also make sense right? | {
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https://api.github.com/repos/huggingface/transformers/issues/14985 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14985/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14985/comments | https://api.github.com/repos/huggingface/transformers/issues/14985/events | https://github.com/huggingface/transformers/issues/14985 | 1,090,889,296 | I_kwDOCUB6oc5BBaZQ | 14,985 | very large model on multi gpu | {
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"Hi @ahtamjan, I would advise you to read this very complete document that @stas00 created: [Transformers docs: Performance and scalability](https://huggingface.co/docs/transformers/master/en/performance#performance-and-scalability-how-to-fit-a-bigger-model-and-train-it-faster)",
"Probably head directly to Deepsp... | 1,640 | 1,644 | 1,644 | NONE | null | I converted XLMR-xxl from fairseq to transformers, and the model is too large to load in one GPU (the model is about 40g). I have 4 V100-32G gpu and how can I fix this problem ? How can I split and load the model to 2 gpus? | {
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https://api.github.com/repos/huggingface/transformers/issues/14984 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14984/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14984/comments | https://api.github.com/repos/huggingface/transformers/issues/14984/events | https://github.com/huggingface/transformers/issues/14984 | 1,090,875,362 | I_kwDOCUB6oc5BBW_i | 14,984 | Finetune M2M on multiple language pairs | {
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"hi, I don't think it's possible :( But you plan to make your model public?",
"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 guid... | 1,640 | 1,647 | 1,647 | NONE | null | Hi @all, I am able to finetune the M2M model for one lang pair using the below script.
CUDA_VISIBLE_DEVICES=0,1,2,3,6 python -m torch.distributed.run --nproc_per_node=5 run_translation.py --model_name_or_path=m2m100_418M_new_token --do_train --do_eval --source_lang ja --target_lang en --fp16=True --evaluation_strate... | {
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https://api.github.com/repos/huggingface/transformers/issues/14983 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14983/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14983/comments | https://api.github.com/repos/huggingface/transformers/issues/14983/events | https://github.com/huggingface/transformers/pull/14983 | 1,090,773,393 | PR_kwDOCUB6oc4wYYFL | 14,983 | Fix Code block speech pretraining example | {
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<!--
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https://api.github.com/repos/huggingface/transformers/issues/14982 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14982/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14982/comments | https://api.github.com/repos/huggingface/transformers/issues/14982/events | https://github.com/huggingface/transformers/pull/14982 | 1,090,736,411 | PR_kwDOCUB6oc4wYQnF | 14,982 | Resubmit changes after rebase to master | {
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"@philschmid @LysandreJik I carried over all my work from the previous serialization.rst to serialization.mdx file per rebase to master. Looking forward to the approval and merge to master branch. ",
"Hi @LysandreJik @philschmid please review this PR and let me know of any suggestions. Thank you."
] | 1,640 | 1,641 | 1,641 | CONTRIBUTOR | null | # What does this PR do?
This PR proposes to add a new section to TorchScript documentation "Deploying HuggingFace TorchScript models on AWS using the Neuron SDK".
Fixes # issue [14425](https://github.com/huggingface/transformers/issues/14425)
## Before submitting
- [x] This PR fixes a typo or improves the do... | {
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https://api.github.com/repos/huggingface/transformers/issues/14981 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14981/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14981/comments | https://api.github.com/repos/huggingface/transformers/issues/14981/events | https://github.com/huggingface/transformers/pull/14981 | 1,090,685,165 | PR_kwDOCUB6oc4wYF7M | 14,981 | Fixing a pathological case for slow tokenizers | {
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Fixes issue found here for slow tokenizers:
https://github.com/huggingface/tokenizers/issues/848
When using arbitrary tokens, a bug could occur where we would seed the new character, even when the lookahead attempted to skip over that part of the text. Thus we could have an extra match ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14980 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14980/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14980/comments | https://api.github.com/repos/huggingface/transformers/issues/14980/events | https://github.com/huggingface/transformers/pull/14980 | 1,090,649,862 | PR_kwDOCUB6oc4wX-rl | 14,980 | [Generate] correct encoder_outputs are passed without attention_mask | {
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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/14979 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14979/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14979/comments | https://api.github.com/repos/huggingface/transformers/issues/14979/events | https://github.com/huggingface/transformers/pull/14979 | 1,090,616,632 | PR_kwDOCUB6oc4wX3uC | 14,979 | Add `with torch.no_grad()` to DistilBERT integration test forward pass | {
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"Thank you for the feedback and confirmation! I've reverted the change. ",
"Hello @jaketae, were your last changes committed? I still see a lot of non-integration tests with `torch.no_grad`",
"@LysandreJik Apologies for the delay! I thought I had properly committed and pushed the changes but seems like that was... | 1,640 | 1,645 | 1,642 | CONTRIBUTOR | null | # What does this PR do?
This PR encapsulates forward passes in DistilBERT unit tests with `with torch.no_grad():` as per #14642.
Also, a unit test seemed to terminate early due to a `return` in a loop; this was replaced with `continue`. (If this was not what was intended, I will rollback the modification.)
## ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14978 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14978/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14978/comments | https://api.github.com/repos/huggingface/transformers/issues/14978/events | https://github.com/huggingface/transformers/issues/14978 | 1,090,534,828 | I_kwDOCUB6oc5BAD2s | 14,978 | How to instantiate custom T5ForConditionalGeneration | {
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I have problems using `T5ForConditionalGeneration`.
I want to evaluate performance of the model without any information from the encoder, i.e., figure out what is the lower bound of decoder performance. To do so, I use a model as follows during both training and validation:
```python
bs = labels.... | {
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https://api.github.com/repos/huggingface/transformers/issues/14977 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14977/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14977/comments | https://api.github.com/repos/huggingface/transformers/issues/14977/events | https://github.com/huggingface/transformers/issues/14977 | 1,090,442,249 | I_kwDOCUB6oc5A_tQJ | 14,977 | Convering tf to torch: How to set custom embedding_size when using load_tf_weights_in_bert? | {
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"Hi,\r\n\r\nIn that case, I would fork the library, and create a new branch that adjusts the word embeddings to be:\r\n\r\n`self.word_embeddings = nn.Embedding(config.vocab_size, config.embedding_size, padding_idx=config.pad_token_id)`\r\n\r\nIf you then convert the checkpoint from your new branch, it will work.",
... | 1,640 | 1,643 | 1,643 | NONE | null | I'm trying to convert a bert-tiny model into torch version and I am using the "load_tf_weights_in_bert" scripts from transformers.
And when I executed the function and fed the right checkpoints and configs, the scripts reported:
ValueError: Pointer shape torch.Size([312]) and array shape (128,) mismatched
After ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14976 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14976/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14976/comments | https://api.github.com/repos/huggingface/transformers/issues/14976/events | https://github.com/huggingface/transformers/issues/14976 | 1,090,439,631 | I_kwDOCUB6oc5A_snP | 14,976 | Model stopped training once I introduced << report_to = 'wandb' >> in TrainingArguments | {
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"@pratikchhapolika can you share a minimum example or a colab? Does it run ok with W&B disabled?\r\n\r\n```\r\nos.environ[\"WANDB_DISABLED\"] = \"true\"\r\n```\r\n\r\nAlso make sure you are on the latest version of W&B, \r\n\r\n```\r\npip install wandb --upgrade\r\n```",
"> @pratikchhapolika can you share a minim... | 1,640 | 1,645 | 1,645 | 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:
```
import wandb
wandb.login()
%env WANDB_LOG_MODEL=true
model = tr.BertForSequenceClas... | {
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https://api.github.com/repos/huggingface/transformers/issues/14975 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14975/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14975/comments | https://api.github.com/repos/huggingface/transformers/issues/14975/events | https://github.com/huggingface/transformers/issues/14975 | 1,090,390,512 | I_kwDOCUB6oc5A_gnw | 14,975 | Custom constructed and trained `tokenizers.Tokenizer` for Albert error. | {
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"Solved.\r\n\r\nTokenizer created、trained、saved in `tokenizers` library, can be loaded in `transformers` library in this way:\r\n```\r\ntokenizer = PreTrainedTokenizerFast(tokenizer_object=Tokenizer.from_file(tkn_path))\r\n```\r\n\r\nSince I'm using tokenizer for mlm tasks, I shall use it in this way:\r\n```\r\ntok... | 1,640 | 1,640 | 1,640 | NONE | null | I created and traind a custom tokenizer for BERT following example in this page: https://huggingface.co/docs/tokenizers/python/latest/pipeline.html
```py
from tokenizers import Tokenizer
from tokenizers.models import WordPiece
bert_tokenizer = Tokenizer(WordPiece(unk_token="[UNK]"))
from tokenizers import norm... | {
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https://api.github.com/repos/huggingface/transformers/issues/14974 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14974/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14974/comments | https://api.github.com/repos/huggingface/transformers/issues/14974/events | https://github.com/huggingface/transformers/issues/14974 | 1,090,356,817 | I_kwDOCUB6oc5A_YZR | 14,974 | How to save the fine-tuned 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)... | 1,640 | 1,644 | 1,644 | NONE | null | Hi,
I save the fine-tuned model with the `tokenizer.save_pretrained(my_dir)` and `model.save_pretrained(my_dir)`. Meanwhile, the model performed well during the fine-tuning(i.e., the loss remained stable at **0.2790**). And then, I use the `model_name.from_pretrained(my_dir)` and ` tokenizer_name.from_pretrained(my_d... | {
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"i was able to fix this issue by installing the correct version"
] | 1,640 | 1,641 | 1,641 | NONE | null | When running the below piece of code:
`from transformers import pipeline
classifier = pipeline("zero-shot-classification",
model="Jiva/xlm-roberta-large-it-mnli", device=0, use_fast=True, multi_label=True)`
the following error occurs:
```
OSError: Can't load config for 'Jiva/xlm-robert... | {
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https://api.github.com/repos/huggingface/transformers/issues/14972 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14972/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14972/comments | https://api.github.com/repos/huggingface/transformers/issues/14972/events | https://github.com/huggingface/transformers/issues/14972 | 1,090,330,351 | I_kwDOCUB6oc5A_R7v | 14,972 | Ability to save model outcomes in tabular format CSV file? | {
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"You need to add your own logging handler.\r\nCheck this: https://github.com/huggingface/transformers/issues/10454",
"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 th... | 1,640 | 1,644 | 1,644 | 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_model",num_lab... | {
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https://api.github.com/repos/huggingface/transformers/issues/14971 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14971/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14971/comments | https://api.github.com/repos/huggingface/transformers/issues/14971/events | https://github.com/huggingface/transformers/issues/14971 | 1,090,284,067 | I_kwDOCUB6oc5A_Goj | 14,971 | [Request] PerceiverForTokenClassification for NER task | {
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"Hi,\r\n\r\nThanks for your interest in Perceiver and for trying it out on a task that is not implemented yet in the library!\r\n\r\nHowever, for a token classification task such as NER, I would actually just take the same decoder settings as `PerceiverForMaskedLM` (as masked language modeling is also solved as a t... | 1,640 | 1,644 | 1,644 | CONTRIBUTOR | null | # 🚀 Feature request
I'm reading [Perceiver IO](https://huggingface.co/blog/perceiver) blog, it says PeceiverIO could also do NER task. So I try to implement a `PerceiverForTokenClassification` model.
I use `conll2003` dataset to test my model. Here is my implement (the script is modified from [run_ner.py](https:... | {
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https://api.github.com/repos/huggingface/transformers/issues/14970 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14970/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14970/comments | https://api.github.com/repos/huggingface/transformers/issues/14970/events | https://github.com/huggingface/transformers/pull/14970 | 1,090,261,402 | PR_kwDOCUB6oc4wWtSF | 14,970 | Replace assertion with exception | {
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Replaces `assert` with `ValueError` as per #12789.
## 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](https://github.com/huggingface/transformers/blob/master/CONTRIBUTI... | {
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https://api.github.com/repos/huggingface/transformers/issues/14969 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14969/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14969/comments | https://api.github.com/repos/huggingface/transformers/issues/14969/events | https://github.com/huggingface/transformers/issues/14969 | 1,090,044,921 | I_kwDOCUB6oc5A-MP5 | 14,969 | Documentation in CTRL linksto 404 | {
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"Nice catch! @stevhliu, would you like to take a look at that?",
"Looks like a [throwback](https://huggingface.co/transformers/v2.2.0/quickstart.html) to `transformers 2.2.0`! Should we point the user to [`CTRLModel.forward()`](https://huggingface.co/docs/transformers/master/en/model_doc/ctrl#transformers.CTRLMod... | 1,640 | 1,646 | 1,646 | MEMBER | null | In https://huggingface.co/docs/transformers/master/en/model_doc/ctrl#overview, when clicking "See reusing the past in generative models", the user is redirected to a 404 (https://huggingface.co/docs/transformers/master/en/quickstart#using-the-past) | {
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https://api.github.com/repos/huggingface/transformers/issues/14968 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14968/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14968/comments | https://api.github.com/repos/huggingface/transformers/issues/14968/events | https://github.com/huggingface/transformers/issues/14968 | 1,090,017,779 | I_kwDOCUB6oc5A-Fnz | 14,968 | GPT-2 generate degenerates into producing garbage after a while | {
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"Hey @demongolem-biz,\r\n\r\nCould you try to turn of \"beam sample\" mode and just use \"sample\" mode instead? Beam sample mode isn't really common for models auch as GPT2.\r\n\r\n```py\r\n tokenizer = GPT2Tokenizer.from_pretrained(\"gpt2\")\r\n # add the EOS token as PAD token to avoid warnings\r\n mode... | 1,640 | 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: 4.9.2
- Platform: Windows 10
- Python version: 3.8.7
- PyTorch version (GPU?): 1.8.1+cu102
- Tensorflow ver... | {
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https://api.github.com/repos/huggingface/transformers/issues/14967 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14967/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14967/comments | https://api.github.com/repos/huggingface/transformers/issues/14967/events | https://github.com/huggingface/transformers/pull/14967 | 1,089,968,260 | PR_kwDOCUB6oc4wVxsP | 14,967 | Update run_speech_recognition_seq2seq.py (max_eval_samples instead of train_samples) | {
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<!--
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https://api.github.com/repos/huggingface/transformers/issues/14966 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14966/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14966/comments | https://api.github.com/repos/huggingface/transformers/issues/14966/events | https://github.com/huggingface/transformers/issues/14966 | 1,089,958,995 | I_kwDOCUB6oc5A93RT | 14,966 | huggingface_pytorch-pretrained-bert_bert.ipynb -- RuntimeError: Cannot find callable bertTokenizer in hubconf | {
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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)... | 1,640 | 1,644 | 1,644 | NONE | null | ## Environment info
Google Colab
https://colab.research.google.com/github/pytorch/pytorch.github.io/blob/master/assets/hub/huggingface_pytorch-pretrained-bert_bert.ipynb#scrollTo=bb1RXLUYj_Wv
- Using GPU in script?: yes
Models:
BERT
## To reproduce
Steps to reproduce the behavior:
```
### First, to... | {
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https://api.github.com/repos/huggingface/transformers/issues/14965 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14965/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14965/comments | https://api.github.com/repos/huggingface/transformers/issues/14965/events | https://github.com/huggingface/transformers/pull/14965 | 1,089,864,586 | PR_kwDOCUB6oc4wVcDs | 14,965 | [Speech Recognition Examples] Update README.md | {
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"Speech Seq2Seq can be advertised as soon as https://github.com/huggingface/transformers/pull/14881 is merged."
] | 1,640 | 1,640 | 1,640 | MEMBER | null | # What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/14964 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14964/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14964/comments | https://api.github.com/repos/huggingface/transformers/issues/14964/events | https://github.com/huggingface/transformers/pull/14964 | 1,089,830,743 | PR_kwDOCUB6oc4wVVah | 14,964 | [Tests] Speed up tokenizer tests | {
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<!--
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https://api.github.com/repos/huggingface/transformers/issues/14963 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14963/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14963/comments | https://api.github.com/repos/huggingface/transformers/issues/14963/events | https://github.com/huggingface/transformers/pull/14963 | 1,089,787,248 | PR_kwDOCUB6oc4wVMVX | 14,963 | Add 'with torch.no_grad()' to BertGeneration integration test forward passes | {
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https://api.github.com/repos/huggingface/transformers/issues/14962 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14962/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14962/comments | https://api.github.com/repos/huggingface/transformers/issues/14962/events | https://github.com/huggingface/transformers/issues/14962 | 1,089,779,158 | I_kwDOCUB6oc5A9LXW | 14,962 | [Speech recognition examples] num_processing_workers not allowed to be set | {
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"Actually, I've seen this error before as well and it confused me a lot as well - thanks a lot for flagging it here @flozi00! I think it only happens though when the audio has to be resampled (like for Common Voice). \r\n\r\n@lhoestq - it's a weird bug with `datasets` I think. I'll try to get a minimum reproducible... | 1,640 | 1,643 | 1,643 | CONTRIBUTOR | 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: master
- Platform: ubuntu
- Python version:
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Usin... | {
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https://api.github.com/repos/huggingface/transformers/issues/14961 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14961/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14961/comments | https://api.github.com/repos/huggingface/transformers/issues/14961/events | https://github.com/huggingface/transformers/pull/14961 | 1,089,768,961 | PR_kwDOCUB6oc4wVIwj | 14,961 | Add 'with torch.no_grad()' to BEiT integration test forward passes | {
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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)... | 1,640 | 1,643 | 1,643 | CONTRIBUTOR | null | # What does this PR do?
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