* Add index.md for tukish language
* Fix index.md (huggingface/transformers#27088)
* Add 'tr' to additional files
* Update docs/source/tr/_toctree.yml
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update index.md
---------
Co-authored-by: Mert Yanık <mert.yanik@lcwaikiki.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* add audio_utils usage in the FE of SpeechToText
* clean unecessary parameters of AudioSpectrogramTransformer FE
* add audio_utils usage in AST
* add serialization tests and function to FEs
* make style
* remove use_torchaudio and move to_dict to FE
* test audio_utils usage
* make style and fix import (remove torchaudio dependency import)
* fix torch dependency for jax and tensor tests
* fix typo
* clean tests with suggestions
* add lines to test if is_speech_availble is False
This commit addresses the 'NoneType' object AttributeError within the IdeficsModel forward function. Previously, the 'device' attribute was accessed directly from input_ids, resulting in a potential 'NoneType' error. Now, the device is properly calculated at the beginning of the forward function and utilized consistently throughout, ensuring the 'image_hidden_states' are derived from the correct device. This modification enables smoother processing and compatibility, ensuring the correct device attribution for 'image_encoder_embeddings' in the IdeficsModel forward pass.
* Removed the redundant SiLUActivation class and now use nn.functional.silu directly.
* I apologize for adding torch.functional.silu. I have replaced it with nn.SiLU.
* Remove redundant variable in feature_extraction file
* Fix error in convert_openai_to_hf.py: "_download() missing 1 required positional argument: root"
* Fix error in convert_openai_to_hf.py: "TypeError: byte indices must be integers or slices, not str"
* Fix decoder_attention_heads value in convert_openai_to_hf.py.
Correct the assignment for `decoder_attention_heads` in the conversion script for the Whisper model.
* Black reformat convert_openai_to_hf.py file.
* Fix Whisper model configuration defaults (for Tiny).
- Correct encoder/decoder layers and attention heads count.
- Update model width (`d_model`) to 384.
* Add docstring to the convert_openai_to_hf.py script with a doctest
* Add shebang and +x permission to the convert_openai_to_hf.py
* convert_openai_to_hf.py: reuse the read model_bytes in the _download() function
* Move convert_openai_to_hf.py doctest example to whisper.md
* whisper.md: Add an inference example to the Conversion section.
* whisper.md: remove `model.config.forced_decoder_ids` from examples (deprecated)
* whisper.md: Remove "## Format Conversion" section; not used by users
* whisper.md: Use librispeech_asr_dummy dataset and load_dataset()
I'm adding accelerate as one of the libraries to install because otherwise when running the Trainer, the model errorr out with the error.
ImportError: Using the `Trainer` with `PyTorch` requires `accelerate>=0.20.1`: Please run `pip install transformers[torch]` or `pip install accelerate -U`
Further context:
1. I've tried this across different environments so I believe that the environment is not the issue.
2. I had the latest transformers library version running.
3. Typically even after install accelerate and import it, it wouldn't resolve the issue until I restart the notebook and try again.
* first batch of structure improvements for model_docs
* second batch of structure improvements for model_docs
* more structure improvements for model_docs
* more structure improvements for model_docs
* structure improvements for cv model_docs
* more structural refactoring
* addressed feedback about image processors
