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I'm trying to run the new `meta-llama/Llama-4-Maverick-17B-128E-Instruct` model with hf/transformers version 4.5.1 on my Mac M4 Max. However, I'm running into:
```
Loading checkpoint shards: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████... | {
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@xenova can the new 17B Lama 4 scout be loaded in the browser or is it much to big?
here is the huggingface collrection:
https://huggingface.co/collections/meta-llama/llama-4-67f0c30d9fe03840bc9d0164
### Motivation
Just a new model that might be able to load in the browser, but probably ... | null | {
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#36963 #37281 #37306 causes regressions with training with deepspeed zero3, see our axolotl integration tests on the latest 4.51.0 release that includes these commits/PRs that all fail with zero3 https://github.com/axolotl-ai-cloud/axolotl/actions/runs/14286223137/job/40041643515
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I have transformers 4.51.0 and am trying to load the Llama 4 Scout model for training. I loaded the safetensor files to disk and am pointing to that location with the `cache_dir` arg. It seems like each time I load the model with `AutoModelForCausalLM` I get a different error. One run it is
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This PR adds `segmentation_maps` support to MobileNetV2ImageProcessor. It also adds `reduce_labels` support and restructures old `preprocess` function to separate `_preprocess`, `_preprocess_image` and `_preprocess_... | {
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As suggested in this issue - #36979 - this PR updates the documentation of the ColPali model, which will now be aligned with the standardized format for all the docs.
## Who can review?
@stevhliu, please let me know if any changes are needed. | {
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As suggested in this issue - https://github.com/huggingface/transformers/issues/36979#issue-2947704577 - this PR updates the documentation of the ColPali model, which will now be aligned with the standardized format for all the docs.
## Who can review?
@stevhliu, please let me know if... | {
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Add ViltImageProcessorFast implementation for faster image processing using PyTorch. (#36978)
This PR adds a fast image processor for the Vilt model that leverages PyTorch and torchvision functions instead of PIL/numpy. The implementation improves performance by using tensor operations and e... | {
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In torch-xla version 2.7, xm.xrt_world_size() is replaced by xr.world_size() and xm.get_ordinal() is replaced by xr.global_ordinal() (xr is "import torch_xla.runtime as xr")
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- `transformers` version: 4.50.3
- Platform: Linux-6.8.0-52-generic-x86_64-with-glibc2.35
- Python version: 3.10.12
- Huggingface_hub version: 0.30.1
- Safetensors version: 0.5.3
- Accelerate version: not installed
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU... | {
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Classes such as `PoolerStartLogits`, `PoolerEndLogits`, `PoolerAnswerClass`, `SQuADHead`, and `SequenceSummary` are:
1. Defined in `modeling_utils.py`, which is somewhat against the main repository philosophy of having classes defined within dedicated modeling files
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But `modeling_utils` has massively changed recently and uses a different code pass for `safetensor` model files - an... | {
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test
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cc @yonigozlan | {
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Now the images/patches are flattened before being processed and passed to the models. This means that the image processing is simplified (no need for padding in the number of images/patches dimension), along with the modeling code ( No more padding ima... | {
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This PR updates the model-card for the DONUT model, as described in [#36979](https://github.com/huggingface/transformers/issues/36979), in an attempt to standardize all model-cards.
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if tha... | {
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"merged_at... | # What does this PR do?
Adding fast processor for OWLv2
Linking: https://github.com/huggingface/transformers/issues/36978
# Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.
CC: @yonigozlan | {
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This PR fixes this issue originally raised in pytorch core https://github.com/pytorch/pytorch/issues/146260 for flex attention on 2.6.0, by setting `mode="max-autotune-no-cudagraphs"`.
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Wrong `working_directory` and got
> OCI runtime exec failed: exec failed: unable to start container process: chdir to cwd ("/transformers") set in config.json failed: no such file or directory: unknown
Also install some packages at specific versions.
The pytest command is running wi... | {
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The following rules are used:
`SIM118` checks for key-existence checks against dict.keys() calls.
`SIM101` duplicate-isinstance-call.
`SIM910` Checks for dict.get() calls that pass None as the default value. | {
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A follow-up work to fix examples. | {
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Some tests were skipped on AMD gpus because they checked `torch.version.cuda` only.
Now we use `IS_CUDA_SYSTEM or IS_ROCM_SYSTEM` | {
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For #37137
Fixes #37238 | {
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Adds `@is_flaky()` to `test_constrained_beam_search_generate_dict_output`. Flake reason in the diff :)
<img width="1049" alt="Screenshot 2025-04-04 at 12 28 29" src="https://github.com/user-attachments/assets/5d729363-bc68-4712-bafe-2b39cc585752" />
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As per title, we added the video loading logic in rush for SmolVLM. But the API is a bit over-complicated, so the decision was to clean up later. As the first step of clean up, we will
- Remove `sampling_fn` from public kwargs, I don't think anyone uses it so we will not deprecate
- Squas... | {
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We suddenly get ``cannot import name 'natten2dav' from 'natten.functional'``, so `dinat` test get `Error` at the beginning of pytest collection, not giving any output, and the slack report job fails due to missing files and we don't receive any report.
I will try to avoid such failure in a... | {
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See the comment in the change. | {
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- `transformers` version: 4.50.0.dev0
- Platform: macOS-15.3.2-arm64-arm-64bit
- Python version: 3.12.9
- Huggingface_hub version: 0.29.3
- Safetensors version: 0.5.3
- Accelerate version: 1.5.2
- Accelerate config: not found
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BC is kept and the models can be loaded as before. All attributes are still available though general config (`config.vocab_size`) but in model code we use `config.text_config` now
Separating out the text config from the general config allows us to support multimodality and text as separate... | {
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This PR adds Optional to remaining types and add `RUF013` rule to enforce that.
RUFF rule `RUF013` checks for the use of implicit Optional in type annotations when the default parameter value is None.
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I have stuck on this problem for a whole week and still cannot figure out why.
Env: python 3.8, transformer -- 4.28
I am using the XLMRobertA Base for finetuning the model for a multi-class classification.
However,
when in the training step, I run trainer.evaluate() it shows the accuracy is 68% while in th... | {
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- `transformers` version: 4.51.0.dev0
- Platform: Linux-5.4.0-208-generic-x86_64-with-glibc2.35
- Python version: 3.11.10
- Huggingface_hub version: 0.30.1
- Safetensors version: 0.5.3
- Accelerate version: 1.6.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU... | {
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Currently, transformer does not support jax version greater than 0.4.13, the libraries has changed and no longer compatible
### Motivation
Currently, transformer does not support jax version greater than 0.4.13, the libraries has changed and no longer compatible
### Your contribution
N/A | {
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"merged_at... | # What does this PR do?
Updated T5 model card with standardized format
Fixes #36979
## Before submitting
- [x] 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/mai... | {
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https://api.github.com/repos/huggingface/transformers/issues/37260 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37260/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37260/comments | https://api.github.com/repos/huggingface/transformers/issues/37260/events | https://github.com/huggingface/transformers/pull/37260 | 2,970,355,648 | PR_kwDOCUB6oc6RTPbP | 37,260 | fix: use mtime by default in Trainer._rotate_checkpoints with automatic fallback | {
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This PR fixes an issue with checkpoint rotation in `transformers.Trainer`. When training with checkpoints saved every 100 steps and a maximum limit of 3 checkpoints, starting a new training session in the same output directory can cause a newly created checkpoint (e.g., `checkpoint-100`) to ... | {
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As @BenjaminBossan found, (https://github.com/huggingface/accelerate/pull/3252), the `TrainingArguments` will set environmental variables automatically when using Accelerate because before it wouldn't work otherwise. Nowadays the only env variable required for things to run smoothly is the on... | null | {
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"merged_at... | # What does this PR do?
The example in the docs for configuring image size doesn't work anymore after the last refactor (https://huggingface.co/docs/transformers/en/model_doc/qwen2_vl#image-resolution-trade-off). This PR ensure backwards compatibility for qwen based image processors
Found when fixing Qwen-Omni wh... | {
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https://api.github.com/repos/huggingface/transformers/issues/37256 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37256/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37256/comments | https://api.github.com/repos/huggingface/transformers/issues/37256/events | https://github.com/huggingface/transformers/pull/37256 | 2,970,138,874 | PR_kwDOCUB6oc6RSgfF | 37,256 | mobilebert model card update | {
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"merged_at... | # What does this PR do?
As suggested in this issue - [Model cards #36979](https://github.com/huggingface/transformers/issues/36979) - this PR updates the documentation of the MobileBERT model, which will now be aligned with the standardized format for all the docs.
## Who can review?
@stevhliu, please let me know ... | {
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"merged_at... | # What does this PR do?
This PR updates the OpenAI GPT model card documentation to better reflect recent improvements and clarifications.
## Before submitting
- [✔️ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ✔️] Did you read the [contributor guideli... | {
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Blip2QFormer is most of the way there already - this PR just:
- Handles A... | {
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"merged_at... | #36979
* Updated the FalconMamba model card
* Second contrib, thank you again for your patience <3
## Before submitting
- [X] 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/transform... | {
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"merged_at... | Reverts huggingface/transformers#37178
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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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```python
from transformers import AutoConfig, AutoModelForCausalLM
config = AutoConfig.from_pretrained("deepseek-ai/DeepSeek-V3-0324")
config.num_hidden_layers = 1
config.intermediate_size = 1024
model = AutoModelForCausalLM.... | {
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✨ Part of the goals to streamline modeling files ✨
This PR abstracts the dynamic RoPE updates, "dynamic" and "longrope", under a decorator. Same capabilities for power users, simpler modeling file.
Review suggestion:
1. `modeling_rope_utils.py`
2. `llama`
3. `phi3` (longrope)
4. ot... | {
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Hello,
Description:
I'm experiencing issues with the Whisper-Large-v3-turbo model when using it for transcription tasks with the Transformers library (version 4.38.3).
Problems:
Incorrect word timestamps: The timestamps generated by the model are not accurate. I've noticed that the timestamps are o... | {
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- `transformers` version: 4.50.0
- Platform: Linux-5.15.0-131-generic-x86_64-with-glibc2.31
- Python version: 3.10.16
- Huggingface_hub version: 0.29.0
- Safetensors version: 0.5.2
- Accelerate version: not installed
- Accelerate config: not found
- DeepSpeed version: not installed
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Before start the work to refactor models, let's make the tests on our base model green 🤗 All tests on llama are green after this PR, except for the flex attention tests (which is a WIP feature)
Fixes:
- `batch_size` -> `max_batch_size` in `StaticCache` (#37007)
- `generate` + FA2 test -... | {
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Transformers import crash if flash attention is installed but not compatible with current torch+cuda version, while we should catch this with `is_flash_attention_2_avaliable`
Fixes #37227
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from langchain_community.document_loaders import WebBaseLoader
from langchain_text_splitters import RecursiveCharacterTextSplitter
from langchain_chroma import Chroma
from langchain_ollama import OllamaEmbeddings
from langchain_ollama import ChatOllama
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During the fine-tuning process of Qwen-OMNI
### Who can help?
During the fine-tuning process of Qwen-OMNI,
using transformer version: transformers-f742a644ca32e65758c3adb36225aef1731bd2a8,
I encountered embedding video issues:
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opencv imshow stuck forever when importing transformer
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supporte... | {
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```
pip install torch==2.0.1 transformers==4.50.3
python <<-EOF
from transformers.integrations import CodeCarbonCallback
EOF
```
results in
```
RuntimeError: Failed to import transformers.integrations.integration_utils because of the following error (look up to see its traceback):
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"merged_at... | # What does this PR do?
Fixed a test regression due to old arg deprecation.
```
RUN_SLOW=1 pytest tests/utils/test_cache_utils.py -k test_static_cache_exportability
```
## Before submitting
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md... | {
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"merged_at... | * Update qwen2.md
* Update qwen2.md
* Update qwen2.md
* Update qwen2.md
* Update docs/source/en/model_doc/qwen2.md
* Update docs/source/en/model_doc/qwen2.md
* Update docs/source/en/model_doc/qwen2.md
* Update docs/source/en/model_doc/qwen2.md
* Update docs/source/en/model_doc/qw... | {
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```
$ python -c "import transformers.modeling_utils"
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/code/users/stas/github/transformers/src/transformers/modeling_utils.py", line 55, in <module>
from .integrations.flas... | {
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"merged_at... | # What does this PR do?
## The problem
Gemma 3 doesn't work with FP16 inference. The cause of it seems to be
1. Embedding output is scaled by sqrt(hidden_size) -> large activations to the transfromer trunk
https://github.com/huggingface/transformers/blob/199d7adf1037e1e3a0a7a2ceb155e468abef5e26/src/transfor... | null | {
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"merged_at... | # What does this PR do?
This PR adds support to use [MLPSpeculator](https://pytorch.org/blog/hitchhikers-guide-speculative-decoding/) models for assisted generation, similar to it's support in [TGI](https://github.com/huggingface/text-generation-inference/pull/1865) and [vLLM](https://github.com/vllm-project/vllm/pull... | null | {
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"merged_at... | # What does this PR do?
- Add classifier head to Donut
- Add image classifier loss to `LOSS_MAPPING`
- Update classifier loss for all swin models
Models:
- vision models: @amyeroberts, @qubvel
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A super minimal abstraction for a layer with gradient checkpointing that keeps the logic for enabling and disabling gradient checkpointing within PreTrainedModel for backward compatibility. It allows for a gradual rollout of the feature by supporting both checkpointing mechanisms: with a the ... | {
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- `transformers` version: 4.49.0
- Platform: Linux-6.8.0-1025-gcp-x86_64-with-glibc2.39
- Python version: 3.11.10
- Huggingface_hub version: 0.29.3
- Safetensors version: 0.5.3
- Accelerate version: 0.34.2
- Accelerate config: - compute_environment: LOCAL_MACHINE
- distributed_type: MULTI_GP... | {
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- `transformers` version: 4.50.3
- Platform: Linux-6.8.0-52-generic-x86_64-with-glibc2.35
- Python version: 3.10.16
- Huggingface_hub version: 0.30.1
- Safetensors version: 0.5.3
- Accelerate version: 1.6.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU?): 2... | {
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"merged_at... | # What does this PR do?
Fixes https://github.com/huggingface/transformers/issues/37051
Approach is to support uneven sharding and seek segments of data that mimics torch.chunk since torch.chunk is the style of sharding adopted by torch `Shard` placements API for both even and uneven sharding. Finally we pass stri... | {
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**System Info:**
- `transformers` version: 4.50.3
- Platform: Linux-6.8.0-52-generic-x86_64-with-glibc2.35
- Python version: 3.10.16
- Huggingface_hub version: 0.30.1
- Safetensors version: 0.5.3
- Accelerate version: 1.6.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch ... | {
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"merged_at... | # What does this PR do?
Follow-up to #37202: add lazy loading to the class-level test dataset 🙌
With recent changes, any test command using a tester that inherits from `PipelineTesterMixin` will trigger the dataset loading for all pipeline tester classes, even if those datasets are never user. For instance, `py... | {
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WIP
For better use of `generate` + `flex_attention` | {
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https://api.github.com/repos/huggingface/transformers/issues/37216 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37216/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37216/comments | https://api.github.com/repos/huggingface/transformers/issues/37216/events | https://github.com/huggingface/transformers/pull/37216 | 2,967,061,369 | PR_kwDOCUB6oc6RIDhB | 37,216 | Detect and use device context manager or global device in `from_pretrained` | {
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As per the title. See https://github.com/huggingface/transformers/pull/37213 as well.
Note that this will only ever be used when no `device_map` is provided, otherwise the `device_map` always take precedence.
This behavior should be aligned with what PyTorch does with contetx manager/global... | {
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https://api.github.com/repos/huggingface/transformers/issues/37215 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37215/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37215/comments | https://api.github.com/repos/huggingface/transformers/issues/37215/events | https://github.com/huggingface/transformers/pull/37215 | 2,967,039,997 | PR_kwDOCUB6oc6RH-33 | 37,215 | A bit of cleaning 🧹🧹 | {
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I stumbled upon the 2 unused functions in `from_pretrained` and they are not used anywhere in the codebase.
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https://api.github.com/repos/huggingface/transformers/issues/37214 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37214/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37214/comments | https://api.github.com/repos/huggingface/transformers/issues/37214/events | https://github.com/huggingface/transformers/pull/37214 | 2,966,958,056 | PR_kwDOCUB6oc6RHtKy | 37,214 | :rotating_light::rotating_light::rotating_light: Replace SetUp with SetUpClass | {
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https://api.github.com/repos/huggingface/transformers/issues/37213 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37213/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37213/comments | https://api.github.com/repos/huggingface/transformers/issues/37213/events | https://github.com/huggingface/transformers/pull/37213 | 2,966,920,628 | PR_kwDOCUB6oc6RHlJG | 37,213 | Fix test | {
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Device context manager is not the intended API to use with `from_pretrained`.
It used to work before, BUT ONLY with `low_cpu_mem_usage=False`, so without consistency.
Will try to investigate if we can easily detect the context and turch it into a simple `device_map` however.
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