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https://api.github.com/repos/huggingface/peft/issues/2415 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2415/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2415/comments | https://api.github.com/repos/huggingface/peft/issues/2415/events | https://github.com/huggingface/peft/issues/2415 | 2,905,929,237 | I_kwDOIf9iDM6tNPYV | 2,415 | size mismatch for lm_head when fintune QWEN2.5 | {
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"total": 0,
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} | null | null | null | ### System Info
transformers version: 4.49.0
Platform: Linux-6.6.0-72.0.0.64.oe2403.x86_64-x86_64-with-glibc2.38
Python version: 3.10.16
Huggingface_hub version: 0.29.1
Safetensors version: 0.5.3
Accelerate version: 1.4.0
Accelerate config: not found
DeepSpeed version: not installed
PyTorch version (GPU?): 2.2.2+cu121... | null | {
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https://api.github.com/repos/huggingface/peft/issues/2413 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2413/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2413/comments | https://api.github.com/repos/huggingface/peft/issues/2413/events | https://github.com/huggingface/peft/issues/2413 | 2,901,962,025 | I_kwDOIf9iDM6s-G0p | 2,413 | `LoraConfig` multiple properties should be unified | {
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"followers_url": "https://api.github.com/users/Qubitiu... | [] | open | false | null | [] | null | 9 | 2025-03-07T04:14:24 | 2025-03-10T14:59:51 | null | CONTRIBUTOR | {
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} | null | null | null | @BenjaminBossan I am trying to add dynamic Lora support to both vLLM and SGLang as LoraConfig already supports this dynamic control via the following variables:
- `rank_pattern`: regex matching of which different `r`/`rank` values are applied
- `exclude_modules`: regex: which modules are not excluded from lora complet... | null | {
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https://api.github.com/repos/huggingface/peft/issues/2412 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2412/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2412/comments | https://api.github.com/repos/huggingface/peft/issues/2412/events | https://github.com/huggingface/peft/issues/2412 | 2,901,275,403 | I_kwDOIf9iDM6s7fML | 2,412 | Lora_B weight becomes 0 when using AuotModel | {
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"total": 0,
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} | null | null | null | ### System Info
transformers version: 4.49.0
peft version: 0.14.0
### Who can help?
@benjaminbossan @sayakpaul
### Information
- [ ] The official example scripts
- [x] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder
- [x] My own task or dataset (give details below)
... | null | {
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https://api.github.com/repos/huggingface/peft/issues/2410 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2410/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2410/comments | https://api.github.com/repos/huggingface/peft/issues/2410/events | https://github.com/huggingface/peft/issues/2410 | 2,899,373,069 | I_kwDOIf9iDM6s0OwN | 2,410 | running forward loop using get_peft_model disables requires_grad on output | {
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} | null | null | null | Hi,
I would like to report a recent issue I have been facing, but I am not sure if it is a bug or I am doing something wrong in the process. The steps to re-create the steps are easy. The issue happens when I try to convert **Qwen2-VL-2B-Instruct** model into a PEFT model using `get_peft_model` method. Simply load the... | null | {
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https://api.github.com/repos/huggingface/peft/issues/2407 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2407/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2407/comments | https://api.github.com/repos/huggingface/peft/issues/2407/events | https://github.com/huggingface/peft/issues/2407 | 2,895,061,583 | I_kwDOIf9iDM6sjyJP | 2,407 | RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cuda:3! (when checking argument for argument mat2 in method wrapper_CUDA_mm) | {
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} | null | null | null | **When I attempted to swap out the Lora configuration in Q-Lora(see qlora.py in _https://github.com/artidoro/qlora_) for Vera, I ran into the following error:**
Traceback (most recent call last):
File "qvera.py", line 859, in <module>
train()
File "qvera.py", line 821, in train
train_result = trainer.train... | null | {
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https://api.github.com/repos/huggingface/peft/issues/2405 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2405/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2405/comments | https://api.github.com/repos/huggingface/peft/issues/2405/events | https://github.com/huggingface/peft/issues/2405 | 2,890,200,666 | I_kwDOIf9iDM6sRPZa | 2,405 | SafetensorError when Merging LoRA Weights | {
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Original Working Environment: Python 3.8, transformers==4.46.0.dev0, safetensors==0.4.4, peft==0.12.0, trl==0.10.1
New Environment with Issue: transformers==4.45.2, safetensors==0.4.4, peft==0.12.0, trl==0.10.1
### Who can help?
_No response_
### Information
- [ ] The official example scripts
... | null | {
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https://api.github.com/repos/huggingface/peft/issues/2400 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2400/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2400/comments | https://api.github.com/repos/huggingface/peft/issues/2400/events | https://github.com/huggingface/peft/issues/2400 | 2,881,481,036 | I_kwDOIf9iDM6rv-lM | 2,400 | processing_class and tokenizer arguments on SFTTrainer() | {
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I got unexpected error from my side when running the example train.py with deepspeed [(link)](https://github.com/huggingface/peft/tree/main/examples/sft)
Argument "**tokenizer**" should be now "**processing_class**".
Could anyone please, let me know whether with the example provided (link above) changing the ... | {
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https://api.github.com/repos/huggingface/peft/issues/2394 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2394/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2394/comments | https://api.github.com/repos/huggingface/peft/issues/2394/events | https://github.com/huggingface/peft/issues/2394 | 2,874,191,172 | I_kwDOIf9iDM6rUK1E | 2,394 | TP + DP training error | {
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"total": 0,
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} | null | null | null | ### System Info
peft: 0.14.1.dev0
transformers: 4.50.dev0
accelerate: 1.4.0.dev0
python: 3.11
linux
### 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
- [ ] My own task or dataset ... | null | {
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https://api.github.com/repos/huggingface/peft/issues/2390 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2390/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2390/comments | https://api.github.com/repos/huggingface/peft/issues/2390/events | https://github.com/huggingface/peft/issues/2390 | 2,866,034,838 | I_kwDOIf9iDM6q1DiW | 2,390 | Bug: Using 2 LoRA configs with `target_modules='all-linear'` leads to nested LoRA layers | {
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-
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder
- [ ] My own task or dataset (give details below)
### Reproduction
```python
from transformers import AutoMode... | {
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https://api.github.com/repos/huggingface/peft/issues/2388 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2388/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2388/comments | https://api.github.com/repos/huggingface/peft/issues/2388/events | https://github.com/huggingface/peft/issues/2388 | 2,863,639,986 | I_kwDOIf9iDM6qr62y | 2,388 | ValueError: Target module Qwen2_5_VisionTransformerPretrainedModel is not supported. | {
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I'm finetuning the Qwen2.5-Vl model with swift for data extraction using LoRA. I'm not sure what is the correct way to save and upload the adapter and be able to recharge it correctly.
In short, I followed these steps
```python
# load model
model, processor = get_model_tokenizer(
'Qwen/Qwen2.5-VL-3B-Inst... | null | {
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https://api.github.com/repos/huggingface/peft/issues/2381 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2381/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2381/comments | https://api.github.com/repos/huggingface/peft/issues/2381/events | https://github.com/huggingface/peft/issues/2381 | 2,857,556,037 | I_kwDOIf9iDM6qUthF | 2,381 | Bug when deleting adapters of a model with modules_to_save | {
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All PEFT versions.
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder
- [ ] My own task or dataset (give details below)
### Reproduction
```python
from transformer... | null | {
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https://api.github.com/repos/huggingface/peft/issues/2379 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2379/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2379/comments | https://api.github.com/repos/huggingface/peft/issues/2379/events | https://github.com/huggingface/peft/issues/2379 | 2,854,940,754 | I_kwDOIf9iDM6qKvBS | 2,379 | prompt_tuning_peft tutorial raises cache layer error | {
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Following the prompt tuning guide leads to an error when executing in a local environment:
- https://huggingface.co/learn/cookbook/en/prompt_tuning_peft
When executing, an exception is raised when calling `model.generate()` with the prompt-tuned model. Everything up to that point seems to be working ... | null | {
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https://api.github.com/repos/huggingface/peft/issues/2377 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2377/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2377/comments | https://api.github.com/repos/huggingface/peft/issues/2377/events | https://github.com/huggingface/peft/issues/2377 | 2,853,540,672 | I_kwDOIf9iDM6qFZNA | 2,377 | Contributing new model merging method to PEFT | {
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Hi all,
I noticed that several model merging methods, such as TIES and DARE, have been implemented in this library, as mentioned [here](https://github.com/huggingface/peft/blob/main/docs/source/developer_guides/model_merging.md).
I was wondering if there is a way for me to contribute a recently ac... | null | {
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https://api.github.com/repos/huggingface/peft/issues/2368 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2368/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2368/comments | https://api.github.com/repos/huggingface/peft/issues/2368/events | https://github.com/huggingface/peft/issues/2368 | 2,838,153,330 | I_kwDOIf9iDM6pKshy | 2,368 | [FSDP] After training embed_tokens in modules_to_save model has hallucinations | {
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"total": 0,
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### Libs
```
absl-py==2.1.0
accelerate==1.3.0
aiohappyeyeballs==2.4.4
aiohttp==3.11.10
aiosignal==1.3.2
annotated-types==0.7.0
asttokens @ file:///home/conda/feedstock_root/build_artifacts/asttokens_1733250440834/work
async-timeout==5.0.1
attrs==24.3.0
beartype==0.14.1
bert-score==0.3.13
better-abc==0.... | {
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https://api.github.com/repos/huggingface/peft/issues/2367 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2367/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2367/comments | https://api.github.com/repos/huggingface/peft/issues/2367/events | https://github.com/huggingface/peft/issues/2367 | 2,838,045,820 | I_kwDOIf9iDM6pKSR8 | 2,367 | Some weights of MistralForSequenceClassification were not initialized from the model checkpoint at mistralai/Mistral-7B-Instruct-v0.3 and are newly initialized: ['score.weight'] | {
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I have been trying to fine tune mistral 7b v0.3 for a downstream task using lora and I get the following warning while running inference.
```python
base_model = AutoModelForSequenceClassification.from_pretrained(
model_id, use_auth_token="hf_***",
num_labels=2,
problem_type="single_label_c... | {
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https://api.github.com/repos/huggingface/peft/issues/2364 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2364/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2364/comments | https://api.github.com/repos/huggingface/peft/issues/2364/events | https://github.com/huggingface/peft/issues/2364 | 2,835,746,171 | I_kwDOIf9iDM6pBg17 | 2,364 | docs: broken links to boft | {
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on page: https://huggingface.co/docs/peft/v0.14.0/en/conceptual_guides/oft
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder
- [ ] My own task or dataset (give d... | {
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https://api.github.com/repos/huggingface/peft/issues/2362 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2362/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2362/comments | https://api.github.com/repos/huggingface/peft/issues/2362/events | https://github.com/huggingface/peft/issues/2362 | 2,833,885,059 | I_kwDOIf9iDM6o6aeD | 2,362 | Import error | {
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"total": 0,
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Successfully installed accelerate-1.3.0 aiohappyeyeballs-2.4.4 aiohttp-3.11.11 aiosignal-1.3.2 bitsandbytes-0.45.1 datasets-3.2.0 dill-0.3.8 frozenlist-1.5.0 huggingface_hub-0.28.1 multidict-6.1.0 multiprocess-0.70.16 pandas-2.2.3 peft-0.14.0 propcache-0.2.1 pyarrow-19.0.0 pytz-2025.1 regex-2024.11.6 s... | {
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https://api.github.com/repos/huggingface/peft/issues/2359 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2359/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2359/comments | https://api.github.com/repos/huggingface/peft/issues/2359/events | https://github.com/huggingface/peft/issues/2359 | 2,829,346,186 | I_kwDOIf9iDM6opGWK | 2,359 | Inconsistent documentation | {
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} | null | null | null | ### System Info
Content of https://huggingface.co/docs/peft/index is not synchronised with ToC.
"How-to guides" is already "PEFT method guides".
"PEFT method guides" are under directory `task_guides`.
### Expected behavior
... | null | {
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https://api.github.com/repos/huggingface/peft/issues/2355 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2355/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2355/comments | https://api.github.com/repos/huggingface/peft/issues/2355/events | https://github.com/huggingface/peft/issues/2355 | 2,823,704,539 | I_kwDOIf9iDM6oTk_b | 2,355 | dataclass config handling | {
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Collecting environment information...
PyTorch version: N/A
Is debug build: N/A
CUDA used to build PyTorch: N/A
ROCM used to build PyTorch: N/A
OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.22.1
Libc version:... | {
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https://api.github.com/repos/huggingface/peft/issues/2354 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2354/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2354/comments | https://api.github.com/repos/huggingface/peft/issues/2354/events | https://github.com/huggingface/peft/issues/2354 | 2,823,156,387 | I_kwDOIf9iDM6oRfKj | 2,354 | Commented PeftConfig | {
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# from .config import PeftConfig, PeftType, PromptLearningConfig, TaskType
@ ./peft/utils/__init__.py
Why?
### 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
- [x]... | {
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https://api.github.com/repos/huggingface/peft/issues/2348 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2348/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2348/comments | https://api.github.com/repos/huggingface/peft/issues/2348/events | https://github.com/huggingface/peft/issues/2348 | 2,811,752,952 | I_kwDOIf9iDM6nl_H4 | 2,348 | Incorrect Magnitude Calculation for DoRA Linear Layers (Violates DoRA Paper Methodology) | {
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} | null | null | null | ### **Description**
The current `DoraLinearLayer` incorrectly computes weight magnitude norms **per input channel** instead of **per output channel**, violating the methodology outlined in the [DoRA paper (Section 3.1)](https://arxiv.org/abs/2402.09353). This leads to degraded performance for linear layers (e.g., in ... | {
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https://api.github.com/repos/huggingface/peft/issues/2344 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2344/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2344/comments | https://api.github.com/repos/huggingface/peft/issues/2344/events | https://github.com/huggingface/peft/issues/2344 | 2,807,348,808 | I_kwDOIf9iDM6nVL5I | 2,344 | FSDP2 and peft | {
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} | null | null | null | Hey, sorry if this is the wrong place. Feel free to move it to discussion.
I am trying to get peft working with fsdp2 and am wondering if someone else attempted that already?
The issue is that Im always getting errors along the lines of:
`RuntimeError: aten.mm.default: got mixed torch.Tensor and DTensor, need to conv... | {
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https://api.github.com/repos/huggingface/peft/issues/2342 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2342/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2342/comments | https://api.github.com/repos/huggingface/peft/issues/2342/events | https://github.com/huggingface/peft/issues/2342 | 2,806,843,497 | I_kwDOIf9iDM6nTQhp | 2,342 | CI: Add gptqmodel to the CI | {
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} | null | null | null | This issue is to track the TODO from [this comment](https://github.com/huggingface/peft/pull/2247#pullrequestreview-2569656574). Once optimum 1.24.0 and transformers 4.49.0 are released, we should enable gptqmodel in the CI (and remove auto-gptq). | null | {
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https://api.github.com/repos/huggingface/peft/issues/2339 | https://api.github.com/repos/huggingface/peft | https://api.github.com/repos/huggingface/peft/issues/2339/labels{/name} | https://api.github.com/repos/huggingface/peft/issues/2339/comments | https://api.github.com/repos/huggingface/peft/issues/2339/events | https://github.com/huggingface/peft/issues/2339 | 2,802,697,166 | I_kwDOIf9iDM6nDcPO | 2,339 | Peft version upgrade from 0.4.0 to 0.14.0 results in "No module named \u0027peft.utils.config\u0027" error | {
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} | null | null | null | ### System Info
Hello,
I'm migrating my sagemaker endpoint from the `huggingface-pytorch-inference:2.1.0-transformers4.37.0-gpu-py310-cu118-ubuntu20.04` image (which is being deprecated) to the `huggingface-pytorch-inference:2.3.0-transformers4.46.1-gpu-py311-cu121-ubuntu20.04-v1.0` image, which is supported.
This n... | {
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