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https://api.github.com/repos/huggingface/transformers/issues/38123 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38123/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38123/comments | https://api.github.com/repos/huggingface/transformers/issues/38123/events | https://github.com/huggingface/transformers/pull/38123 | 3,062,338,916 | PR_kwDOCUB6oc6WHzTb | 38,123 | Minor llama4 fixes | {
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"merged_at... | # What does this PR do?
Fixes a couple nits/wrong defaults in Llama4 code for DynamicCache init - not sure we should even default to it, I think.
The scaling however has to be passed else `eager_attention_forward" will fail. | {
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- `transformers` version: 4.52.0.dev0
- Platform: Linux-5.4.17-2136.339.5.el8uek.x86_64-x86_64-with-glibc2.35
- Python version: 3.10.13
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I run the tests `RUN_SLOW=1 pytest tests/models/emu3/test_modeling_emu3.py::Emu3IntegrationTest::tes
t_model_generate_images` on A100.
The groud truth image is like:
In the latest main branch. The output images ... | {
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I noticed from https://github.com/huggingface/transformers/issues/37849#issuecomment-2837928929 that huggingface plans to convert phi4 MM model to HF format. However, I noticed the PR has been inactive for a while: https://huggingface.co/microsoft/Phi-4-multimodal-instruct/discussions/70. I wonde... | {
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```
import os
import argparse
import torch
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms
from PIL import Image
from transformers import SegformerConfig, SegformerForSemanticSegmentation
from optimum.quanto import quantize, qint8,... | {
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transformers==4.51.2
torch==2.5.0
torchvision==0.20.0
Miscellnous pkg version
Package Version
------------------------- -----------
accelerate 1.6.0
aiofiles 23.2.1
aiohappyeyeballs 2.6.1
aiohttp 3.11.16
aiosignal ... | {
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- `transformers` version: 4.52.0.dev0
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- Safetensors version: 0.5.2
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Some small bug just generate first 2 beams ok, and after just repeats the second one. It happens in around 5 percent... | {
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It is claimed that qwen2-vl supports static KV cache and `torch.compile` in this issue: https://github.com/huggingface/transformers/issues/28981. However, this is not true: the `_supports_static_cache` attribute is disabled in `modeling_qwen2_vl.py` (see: https://github.com/huggingface/transformers... | {
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This PR changes the default behavior of Flax→PyTorch conversion to always allocate real CPU tensors (by setting ```low_cpu_mem_usage=False``` in ```from_pretrained)``` and replaces the old offload logic in ```save_pretrained``` with an up-front detach-and-clone of the entire state_dict. This gu... | null | {
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"merged_at... | Fix typo in torch.compile method parameters
# What does this PR do?
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Added CausalLM support for ModernBert as part of #35385. If there are no issues, I plan to follow up with a commit enabling its use in EncoderDecoderModel.
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When a model is quantized using TP, the save_pretrained() need to support TP when quantization is done and export to model to safetensor file.
The modification will combine the DTensor to full tensor in process which rank = 0 and export the result, for process with other rank number, the e... | null | {
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I obtained the values using the original code reproducer scripts (see test descriptions), which I ran on T4 runners.
cc @ydshieh 😊
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- [x] Flex Attention for all base attention types (encoder, decoder, encoder-decoder cross)
- [x] New Attention Interface for a bunch of models (mostly based on Bart's implementation)
- [x] As a bonus, some models have already been refactored into modular if seen fit, e... | {
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During bisecting, it uses
> elif f"{target_test} FAILED" in result.stdout:
to determine a commit fails a test or not.
However, since #35912, the output is kind altered with `live log call`, and the results are wrong (it think every commit passes).
This PR fixes the issue by checki... | {
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More typing in `TrainingArguments` | {
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Now that we have video processors separate from image processors, the next step is to keep all video-specific processing there. This PR refactors how we sample video frames
Before:
- Frames can be sampled only with `apply_chat_template` and require one to pass a callable `sampling_fn` for... | {
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Fixes a few tests that started failing after https://github.com/huggingface/transformers/pull/35206 | {
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cc @hanouticelina @Wauplin @ydshieh @ArthurZucker | {
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When training with deepspeed and `WANDB_LOG_MODEL` is enabled, on train end, a fake trainer is created on the train end to create artifacts, but results in https://gist.github.com/winglian/e4640bb86860678ba2415cde54d986f4
This removes deepspeed from the args to workaround that issue.
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Fixes https://github.com/huggingface/transformers/issues/38095
`apex.amp` is deprecated, so we need to make sure the user have access to `amp` when they set `half_precision_backend = "apex"`. Also we remove import at the beginning of trainer.py file and import it when needed. | {
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As per title, we should skip the test and fix later | {
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None
### Who can help?
@zucchini-nlp @eustlb
### Information
- [x] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)
### Reproduction
When ... | {
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BatchEncoding.to() only takes ```device``` and ```non_blocking```. but need to take ```dtype``` also
### Motivation
I tested qwen2.5-3B-instruct model.
but
```python
inputs = processor(**input, return_tensors='pt').to(device=model.device, dtype=model.dtype)
```
can't work. because processor re... | {
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https://github.com/NVIDIA/apex/issues/1902 | {
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"merged_at... | When preparing the causal attention mask at this point the mask comes in as a float tensor with min value as a masked value.
It is not correct to convert it to bool and treat it as a bool mask as this inverts the mask. `torch.nn.functional.scaled_dot_product_attention` expects that a bool masked value is `False`.
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https://api.github.com/repos/huggingface/transformers/issues/38093 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38093/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38093/comments | https://api.github.com/repos/huggingface/transformers/issues/38093/events | https://github.com/huggingface/transformers/pull/38093 | 3,058,002,323 | PR_kwDOCUB6oc6V5Jsz | 38,093 | update `require_read_token` | {
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"merged_at... | # What does this PR do?
update `require_read_token`.
Currently, that decorator only works with function/method, but not for a class. The usage of it on classes will skip all the tests in those classes.
This PR fixes this issue. | {
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Fix small issue with InternVL interpolate_pos_encoding function, and add InternVL to video_processing_auto (currently all integration tests are crashing on main).
Cc @zucchini-nlp for video processor | {
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"merged_at... | # What does this PR do?
The existing logic is we inspect model's forward and dataset's return dict keys() and drop unused keys. A simplest scenario where this logic will fail is if I return raw text and label from dataset class and then tokenize in collate_fn. Since model is not expecting the raw text as an input, w... | {
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https://api.github.com/repos/huggingface/transformers/issues/38090 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38090/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38090/comments | https://api.github.com/repos/huggingface/transformers/issues/38090/events | https://github.com/huggingface/transformers/pull/38090 | 3,057,683,592 | PR_kwDOCUB6oc6V4E5s | 38,090 | Refactor `get_XXX_dataloader` from Trainer | {
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Refactors dataloader functions in Trainer | {
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https://api.github.com/repos/huggingface/transformers/issues/38089 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38089/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38089/comments | https://api.github.com/repos/huggingface/transformers/issues/38089/events | https://github.com/huggingface/transformers/pull/38089 | 3,057,574,329 | PR_kwDOCUB6oc6V3tN6 | 38,089 | Omit creation of positional IDs within ESM if applicable | {
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https://api.github.com/repos/huggingface/transformers/issues/38088 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38088/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38088/comments | https://api.github.com/repos/huggingface/transformers/issues/38088/events | https://github.com/huggingface/transformers/pull/38088 | 3,057,561,140 | PR_kwDOCUB6oc6V3qY6 | 38,088 | Disable report callbacks for certain training tests | {
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"merged_at... | This fixes the `No module named 'pynvml'` error in the affected tests on non-cuda devices.
~It does not address `test_auto_batch_size_finder` however, as that test runs `run_glue.py` directly.~
I tried adding `--report_to none` as an argument to the `run_glue.py` call. I'll check if it actually works. | {
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https://api.github.com/repos/huggingface/transformers/issues/38087 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38087/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38087/comments | https://api.github.com/repos/huggingface/transformers/issues/38087/events | https://github.com/huggingface/transformers/pull/38087 | 3,057,325,406 | PR_kwDOCUB6oc6V23qH | 38,087 | Add optional RMSNorm support to BitNet quantization (config + layers) | {
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**Adds optional RMSNorm support to BitNet-style quantisation.**
* Introduces `use_rms_norm` (bool, default False) and `rms_norm_eps` (float, default `1e-6`) to **`BitNetQuantConfig`** so the flag is serialisable via `save_pretrained / from_pretrained`.
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"merged_at... | This PR moves the specialized `MambaCache` class from `cache_utils.py` to `src/transformers/models/mamba/modeling_mamba.py`. This is preliminary work for #38077.
**Changes:**
- Moved `MambaCache` to its own file, aligning with Zamba, Bamba, etc.
- Removed unnecessary Mamba-specific code from `generate`.
- Added M... | {
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"merged_at... | # What does this PR do?
Snippet:
```python
import time
import datasets
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers.generation import GenerationConfig
torch.set_float32_matmul_precision("high")
model_id = "meta-llama/Llama-3.2-3b-Instruct"
model = Auto... | {
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"merged_at... | # What does this PR do?
llava-onevision should not use anyres patching for multi-image case
Fixes https://github.com/huggingface/transformers/issues/34585
## 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 [contri... | {
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"merged_at... | # What does this PR do?
`kernels` may give different outputs (within 1e-5 range) even with the same model (weights) and the same inputs.
https://huggingface.slack.com/archives/C01NE71C4F7/p1747055897244909 | {
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Fixes https://github.com/huggingface/transformers/issues/38053. Images cannot attend to future images but in current implementation we unmask attention within all images
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</br></br>
from [Autoawq](https://github.com/casper-hansen/AutoAWQ)
```markdown
Important Notice:
- AutoAWQ is officially deprecated and will no longer be maintained.
- T... | {
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"merged_at... | ## Overview
This PR introduces a layered architecture for the cache system, allowing for better composition of caches.
## Current class structure
```mermaid
graph TD
B[Cache]
B --> F[StaticCache]
B --> I[HybridCache]
B --> G[DynamicCache]
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"merged_at... | This PR fixes an issue in Qwen2VLImageProcessor where the current implementation does not correctly handle cases when the number of video frames is not divisible by `temporal_patch_size`.
### Problem:
The existing logic repeats the last frame `temporal_patch_size` - 1 times. This works correctly when `temporal_patc... | {
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"merged_at... | # What does this PR do?
Fixes https://github.com/QwenLM/Qwen2.5-VL/issues/1195 just a small typo🤗
Related PR #37033 @zucchini-nlp | {
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Fix description and formatting errors:
1. Fix: Two `True` exists in one conditional statement.
2. Removed line breaks to comply with the doc guideline: 'No need to indent further for the elements building the return.'
Origin:
```
Return:
`torch.BoolTensor`. (`torch.BoolTen... | {
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"merged_at... | ## What does this PR do?
When running the `run_wav2vec2_pretraining_no_trainer.py` example, I got `fsspec.exceptions.FSTimeoutError`.
The reason is that the default timeout (5 * 60s) for the `aiohttp` library used internally by fsspec is too short for large files, e.g. 5.9G.
I also found an issue discussed in t... | {
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I had implemented some batching both using pipeline and model.generate method and for Qwen3 and Llama4 models it shows decoder only model detected so padding should mentioned in left. Which is weird as I inspected the model output and it was totally fine.
However when I mentioned padding to be left, ... | {
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Version: 4.52.0.dev0
In modeling_utils.py, line 236, qwen2_5_vl is misspelled as qwem2_5_vl
<img width="487" alt="Image" src="https://github.com/user-attachments/assets/9a0a6c2b-fc6f-4c17-9a5c-926c67cea597" />
This will cause the load of _checkpoint_conversion_mapping in line 4113 being skipped and ... | {
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# What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/38067 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38067/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38067/comments | https://api.github.com/repos/huggingface/transformers/issues/38067/events | https://github.com/huggingface/transformers/pull/38067 | 3,054,657,577 | PR_kwDOCUB6oc6Vt-rM | 38,067 | Fix bug in prefill_chunk_size that ignores disable_compile flag | {
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"merged_at... | This PR fixes a bug in the `prefill_chunking` function where the compilation check is not performed before calling `get_compiled_call()`.
When using `prefill_chunk_size > 0` in a `GenerationConfig`, the model's forward function is always compiled, even if `disable_compile=True` is specified. This happens because th... | {
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https://api.github.com/repos/huggingface/transformers/issues/38066 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38066/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38066/comments | https://api.github.com/repos/huggingface/transformers/issues/38066/events | https://github.com/huggingface/transformers/issues/38066 | 3,054,509,355 | I_kwDOCUB6oc62EB0r | 38,066 | `AutoModel.from_pretrained(...)` (with explicit `device_map` unset) fails under `with torch.device("meta")` with PyTorch 2.6.0 and 2.7.0 | {
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# from torch.nn.attention.flex_attention import BlockMask, flex_attention
from transformers import AutoModel
import torch
with torch.device('meta'):
AutoModel.from_pretrained('Qwen/Qwen2.5-0.5B', trust_remote_code=True)
````
I found this code in the wild in https://github.com/Open-Reasoner-Zero/Open-Rea... | {
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https://api.github.com/repos/huggingface/transformers/issues/38065 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38065/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38065/comments | https://api.github.com/repos/huggingface/transformers/issues/38065/events | https://github.com/huggingface/transformers/issues/38065 | 3,054,490,539 | I_kwDOCUB6oc62D9Or | 38,065 | [minor] Protect against broken/missing torchvision installations and do not hard-fail at timm/torchvision import (many text models don't need any timm/torchvision as hard dependencies) | {
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### System Info
Google Colab, uses pytorch 2.6.0 for now
### Who can help?
_No response_
### Information
- [ ] The ... | {
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https://api.github.com/repos/huggingface/transformers/issues/38064 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38064/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38064/comments | https://api.github.com/repos/huggingface/transformers/issues/38064/events | https://github.com/huggingface/transformers/pull/38064 | 3,054,476,222 | PR_kwDOCUB6oc6Vta9d | 38,064 | Added scores in the streamer classes based on generation flag | {
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"merged_at... | This PR works on a personal issue I had when creating a JSON formatter.
I needed to know the tokens' scores as soon as they were ready; as such, I created 2 new classes that inherit BaseStreamer to support Immediate token output and forwarded the scores from each generate function into the streamer put method.
## B... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/38063 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38063/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38063/comments | https://api.github.com/repos/huggingface/transformers/issues/38063/events | https://github.com/huggingface/transformers/issues/38063 | 3,054,470,178 | I_kwDOCUB6oc62D4Qi | 38,063 | Adding native support to load GGUF models using transformers | {
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] | open | false | null | [] | null | [] | 2025-05-10T19:02:53 | 2025-07-31T08:21:08 | null | NONE | null | null | null | null | ### Feature request
GGUF recently became a popular model format that can be used to load ridiculously large models in 2x3090 (48GB) cards. While loading the original models are still better and HF supports 4bit and 8bit but those quant aren't much practical for very large models unlike GGUF.
Llama CPP exists and its... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/38062 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38062/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38062/comments | https://api.github.com/repos/huggingface/transformers/issues/38062/events | https://github.com/huggingface/transformers/pull/38062 | 3,054,457,959 | PR_kwDOCUB6oc6VtW-d | 38,062 | Fix broken example generation script for Llama3 | {
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Running this script with Llama3 fails with error:
```
...
--> 316 return _sentencepiece.SentencePieceProcessor_LoadFromFile(self, arg)
TypeError: not a string
```
As mentioned in #30607 this is because Llama3 tokenizer is not based on sentencepiece. The fix is to use `AutoTokenize... | {
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- `transformers` version: 4.51.3
- Platform: macOS-14.4.1-arm64-arm-64bit
- Python version: 3.9.19
- Huggingface_hub version: 0.30.2
- Safetensors version: 0.4.3
- Accelerate version: 1.2.1
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU?): 2.7.0 (False)
- Tens... | {
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EDIT: submitting this for review since the per-layer refactor is a thing on its own. Happy to merge this small improvement. | {
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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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This PR updates the `repo_id` used in the docs of SAM-HQ (as it was updated to https://huggingface.co/syscv-community/sam-hq-vit-base)
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work for `pip install git+https://github.com/huggingface/transformers@7a3e208892c06a5e278144eaf38c8599a42f53e7`
not work `main`
https://github.com/QwenLM/Qwen2.5-VL/issues/1192
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [x] My own modified scripts
### Tas... | {
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"merged_at... | # What does this PR do?
This PR implements our recent work **SQuat** ([arXiv:2503.24358](https://arxiv.org/abs/2503.24358)) for **KV cache quantization** in Transformers. SQuat introduces a method for orthogonally projecting keys to a query subspace, improving the accuracy of quantized attention computation.
Key ... | null | {
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"merged_at... | ## Pull Request: Add Support for Handling Overlapping Annotations in Mask2Former
### Problem
The current image processing pipeline for Mask2Former doesn't handle overlapping annotations correctly. When annotations overlap, the processing order is arbitrary, causing larger objects to sometimes be overwritten by sm... | null | {
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As per the attention mask example in the Gemma3 blog (https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/gemma3/attention-ascii.png), it looks like there is non-causal attention within the image and causal attention across images (i.e., an image does not attend to a futu... | {
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(venv) nicholas@B367309:tmp(master)$ transformers-cli env
Copy-and-paste the text below in your GitHub issue and FILL OUT the two last points.
- `transformers` version: 4.51.1
- Platform: Linux-5.10.16.3-microsoft-standard-WSL2-x86_64-with-glibc2.39
- Python version: 3.12.3
- Huggingface_hub version:... | {
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"merged_at... | # What does this PR do?
As per title, the recent refactor broke loading for some models. The tests were ran before the last commit when a restriction on model names was added, thus the issue went unnoticed while merging 🥲
fixes https://github.com/huggingface/transformers/issues/38056, and fixes https://gith... | {
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transformers==4.52.0.dev0 (Top of the Trunk)
Platform: Rocky Linux
Traceback (most recent call last):
File ".local/lib/python3.9/site-packages/peft/tuners/lora/model.py", line 359, in __getattr__
return super().__getattr__(name) # defer to nn.Module's logic
File ".local/lib/python3.9/site-pac... | {
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"merged_at... | # What does this PR do?
With the power of `@overload` this PR adds several features to make our pipelines more IDE-friendly (and as a bonus more Curosor, Copilot and autocompletion friendly).
### 1. Correctly resolve pipeline `type` in case `task` is specified for pipeline function
![pipe_type](https://github.... | {
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- Fixes a shallow‐copy bug in `GroundingDinoMLPPredictionHead` when `config.decoder_bbox_embed_share=False`:
- Previously all decoder layers shared the same head instance.
- Now each layer builds its own `GroundingDinoMLPPredictionHead` and wraps them in a `nn.ModuleList`.
- Adds a ne... | {
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The main goal of this PR is to enable user-friendly `generate` parameterization. This also facilitates performance-related customization, which will be the focus of a follow-up PR.
After the deprecation cycle, new users typing `transformers chat -h` will be redirected to a (new) [docs intr... | {
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As per the title. https://github.com/huggingface/transformers/pull/37873 broke the cache update when going beyond the sliding window, see my comment [here](https://github.com/huggingface/transformers/pull/37873#discussion_r2081837193).
This PR fixes it.
This also incorporates the issue men... | {
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Fixes https://github.com/huggingface/transformers/issues/38002. Sliding mask should not be applied when `config.use_sliding_window = False`
Added a small test as well
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When running `BeitImageProcessorFast` with `do_reduce_labels=True`, it not only reduces labels in segmentation map, but also applies `reduce_label` to the image itself
`reduce_label` should be applied only to segmentation maps
### Test
```py
import transformers
import torch
pr... | {
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With `CircleCI-Public/trigger-circleci-pipeline-action@v1.2.0`, we could specify `target-branch` 🎉 | {
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Support request for passing a custom 3D attention mask to a modernbert model.
Currently it only supports 2D attention mask of bs, seq_len [modeling_modernbert.py#L859](https://github.com/huggingface/transformers/blob/774dc274ac966f4bccbcd90d55bba23f6cca37ae/src/transformers/models/modernbert/modeli... | null | {
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- `transformers` version: 4.51.3
- Platform: Linux-6.11.0-25-generic-x86_64-with-glibc2.39
- Python version: 3.12.3
- Huggingface_hub version: 0.30.2
- 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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In #37885, we use a Github Action workflow file to trigger CircleCI via API. We use `pull_requesttarget` event to allow the Github Actions workflow being triggered without an approval, but this leads to the triggered CircleCI checkout to the `main` branch, which is the wrong target to test ag... | {
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https://api.github.com/repos/huggingface/transformers/issues/38037 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38037/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38037/comments | https://api.github.com/repos/huggingface/transformers/issues/38037/events | https://github.com/huggingface/transformers/pull/38037 | 3,051,341,451 | PR_kwDOCUB6oc6ViwvX | 38,037 | Fix an error in STOPPING_CRITERIA_INPUTS_DOCSTRING | {
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There is an error in the comment `STOPPING_CRITERIA_INPUTS_DOCSTRING` for `StoppingCriteria`:
```
`True` indicates we should continue.
```
Should be
```
`False` indicates we should continue.
```
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss t... | {
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https://api.github.com/repos/huggingface/transformers/issues/38035 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38035/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38035/comments | https://api.github.com/repos/huggingface/transformers/issues/38035/events | https://github.com/huggingface/transformers/issues/38035 | 3,051,150,804 | I_kwDOCUB6oc613N3U | 38,035 | Setting average_tokens_across_devices to True caused an error because it attempted to gather CPU tensors using NCCL. | {
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python = 3.9
torch = 2.7.0+cu128
transformers = 4.51.3
### Who can help?
_No response_
### Information
- [x] The official example scripts
- [ ] My own modified scripts
### Tasks
- [x] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (g... | {
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https://api.github.com/repos/huggingface/transformers/issues/38033 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38033/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38033/comments | https://api.github.com/repos/huggingface/transformers/issues/38033/events | https://github.com/huggingface/transformers/issues/38033 | 3,050,714,135 | I_kwDOCUB6oc611jQX | 38,033 | RuntimeError when loading InternVL3-14B model: Embedding size mismatch | {
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When trying to load the [InternVL3-14B](https://huggingface.co/OpenGVLab/InternVL3-14B) model using the `transformers` library, I encountered the following error:
```
RuntimeError: Error(s) in loading state_dict for Embedding:
size mismatch for weight: copying a param with shape torch.Size([1516... | {
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transformers version: 4.50.2
python version: 3.13.1
### Who can help?
@zach-huggingface @SunMarc
### Information
- [ ] The official example scripts
- [x] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
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This PR fixes a bug in the `GroundingDino` model implementation related to how the `bbox_embed` layers are instantiated when `decoder_bbox_embed_share=False`.
In the previous code, the same `GroundingDinoMLPPredictionHead` instance was reused across decoder layers, resulting in a shallow c... | {
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https://api.github.com/repos/huggingface/transformers/issues/38030 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38030/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38030/comments | https://api.github.com/repos/huggingface/transformers/issues/38030/events | https://github.com/huggingface/transformers/pull/38030 | 3,050,338,132 | PR_kwDOCUB6oc6VgWtj | 38,030 | Add `TemplateConstraint` and `OrdredConstraint` features (#27706) | {
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https://api.github.com/repos/huggingface/transformers/issues/38029 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38029/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38029/comments | https://api.github.com/repos/huggingface/transformers/issues/38029/events | https://github.com/huggingface/transformers/pull/38029 | 3,050,246,743 | PR_kwDOCUB6oc6VgHP5 | 38,029 | Update Loss Functions to Accept Tensor num_items_in_batch | {
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"merged_at... | This PR updates the ForCausalLMLoss and ForMaskedLMLoss functions to handle num_items_in_batch as a torch.Tensor instead of an int, aligning with how the parameter is actually passed during training.
Changes:
Updated num_items_in_batch: Optional[int] → Optional[torch.Tensor] in both functions.
Applied .item() ... | {
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https://api.github.com/repos/huggingface/transformers/issues/38028 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38028/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38028/comments | https://api.github.com/repos/huggingface/transformers/issues/38028/events | https://github.com/huggingface/transformers/issues/38028 | 3,050,087,597 | I_kwDOCUB6oc61zKSt | 38,028 | bug in new prefill_chunk_size implementation | {
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Hi, I noticed a bug in the new chunked prefill code: the implementation does not check whether or not the forward method is compilable, as is done elsewhere in the code.
Specifically, https://github.com/huggingface/transformers/blob/d231f5a7d4d110fffe91ba31b4995c8574036c14/src/transformers/generation/... | {
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https://api.github.com/repos/huggingface/transformers/issues/38027 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38027/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38027/comments | https://api.github.com/repos/huggingface/transformers/issues/38027/events | https://github.com/huggingface/transformers/issues/38027 | 3,049,598,465 | I_kwDOCUB6oc61xS4B | 38,027 | TimeSformer assumes a fixed number of frames in its layers even though it interpolates temporal embeddings based on the input | {
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- `transformers` version: 4.52.0.dev0
- Platform: Linux-6.11.0-24-generic-x86_64-with-glibc2.39
- Python version: 3.12.3
- Huggingface_hub version: 0.30.2
- 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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https://api.github.com/repos/huggingface/transformers/issues/38026 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38026/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38026/comments | https://api.github.com/repos/huggingface/transformers/issues/38026/events | https://github.com/huggingface/transformers/pull/38026 | 3,049,367,030 | PR_kwDOCUB6oc6VdHch | 38,026 | Pass `eps` to `Mistral3RMSNorm` | {
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"merged_at... | # What does this PR do?
Fixes #38025
This solution is part of the investigation detailed [here](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/74)
@qubvel
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https://api.github.com/repos/huggingface/transformers/issues/38025 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38025/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38025/comments | https://api.github.com/repos/huggingface/transformers/issues/38025/events | https://github.com/huggingface/transformers/issues/38025 | 3,049,356,202 | I_kwDOCUB6oc61wXuq | 38,025 | `eps` is not passed in `Mistral3RMSNorm` | {
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https://github.com/huggingface/transformers/blob/f2909e024cca9b7846030a91d7d4cafbf0f6208d/src/transformers/models/mistral3/modeling_mistral3.py#L49
but when used in the creation of the Mistral3 model, it is not actually passed
https://github.com/huggingface/transformers... | {
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https://api.github.com/repos/huggingface/transformers/issues/38024 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38024/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38024/comments | https://api.github.com/repos/huggingface/transformers/issues/38024/events | https://github.com/huggingface/transformers/issues/38024 | 3,049,277,563 | I_kwDOCUB6oc61wEh7 | 38,024 | while using trainer to train mnist model, 'ValueError: Found input variables with inconsistent numbers of samples: [10000, 8750]' | {
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https://api.github.com/repos/huggingface/transformers/issues/38023 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38023/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38023/comments | https://api.github.com/repos/huggingface/transformers/issues/38023/events | https://github.com/huggingface/transformers/pull/38023 | 3,049,151,697 | PR_kwDOCUB6oc6VcYKU | 38,023 | [ESM] Add flash-attention-2 backend for ESM-2 | {
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Implements the flash-attention-2 attention backend for ESM-2.
ESM-2 is a BERT-based protein language model from facebook research. While the model is undoubtedly a bit old at this point - there are now ESM-3 and ESM-C models available, they remain very popular on the huggingface hub with ... | {
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