Update peft requirement from ==0.6.* to ==0.7.*

[dependabot]

Updates the requirements on peft to permit the latest version.

Release notes

Sourced from peft's releases.

v0.7.0: Orthogonal Fine-Tuning, Megatron support, better initialization, safetensors, and more

Highlights

• Orthogonal Fine-Tuning (OFT): A new adapter that is similar to LoRA and shows a lot of promise for Stable Diffusion, especially with regard to controllability and compositionality. Give it a try! By @​okotaku in huggingface/peft#1160
• Support for parallel linear LoRA layers using Megatron. This should lead to a speed up when using LoRA with Megatron. By @​zhangsheng377 in huggingface/peft#1092
• LoftQ provides a new method to initialize LoRA layers of quantized models. The big advantage is that the LoRA layer weights are chosen in a way to minimize the quantization error, as described here: https://arxiv.org/abs/2310.08659. By @​yxli2123 in huggingface/peft#1150.

Other notable additions

• It is now possible to choose which adapters are merged when calling merge (#1132)
• IA³ now supports adapter deletion, by @​alexrs (#1153)
• A new initialization method for LoRA has been added, "gaussian" (#1189)
• When training PEFT models with new tokens being added to the embedding layers, the embedding layer is now saved by default (#1147)
• It is now possible to mix certain adapters like LoRA and LoKr in the same model, see the docs (#1163)
• We started an initiative to improve the documenation, some of which should already be reflected in the current docs. Still, help by the community is always welcome. Check out this issue to get going.

Migration to v0.7.0

• Safetensors are now the default format for PEFT adapters. In practice, users should not have to change anything in their code, PEFT takes care of everything -- just be aware that instead of creating a file adapter_model.bin, calling save_pretrained now creates adapter_model.safetensors. Safetensors have numerous advantages over pickle files (which is the PyTorch default format) and well supported on Hugging Face Hub.
• When merging multiple LoRA adapter weights together using add_weighted_adapter with the option combination_type="linear", the scaling of the adapter weights is now performed differently, leading to improved results.
• There was a big refactor of the inner workings of some PEFT adapters. For the vast majority of users, this should not make any difference (except making some code run faster). However, if your code is relying on PEFT internals, be aware that the inheritance structure of certain adapter layers has changed (e.g. peft.lora.Linear is no longer a subclass of nn.Linear, so isinstance checks may need updating). Also, to retrieve the original weight of an adapted layer, now use self.get_base_layer().weight, not self.weight (same for bias).

What's Changed

As always, a bunch of small improvements, bug fixes and doc improvements were added. We thank all the external contributors, both new and recurring. Below is the list of all changes since the last release.

• After release: Bump version to 0.7.0.dev0 by @​BenjaminBossan in huggingface/peft#1074
• FIX: Skip adaption prompt tests with new transformers versions by @​BenjaminBossan in huggingface/peft#1077
• FIX: fix adaptation prompt CI and compatibility with latest transformers (4.35.0) by @​younesbelkada in huggingface/peft#1084
• Improve documentation for IA³ by @​SumanthRH in huggingface/peft#984
• [Docker] Update Dockerfile to force-use transformers main by @​younesbelkada in huggingface/peft#1085
• Update the release checklist by @​BenjaminBossan in huggingface/peft#1075
• fix-gptq-training by @​SunMarc in huggingface/peft#1086
• fix the failing CI tests by @​pacman100 in huggingface/peft#1094
• Fix f-string in import_utils by @​KCFindstr in huggingface/peft#1091
• Fix IA3 config for Falcon models by @​SumanthRH in huggingface/peft#1007
• FIX: Failing nightly CI tests due to IA3 config by @​BenjaminBossan in huggingface/peft#1100
• [core] Fix safetensors serialization for shared tensors by @​younesbelkada in huggingface/peft#1101
• Change to 0.6.1.dev0 by @​younesbelkada in huggingface/peft#1102
• Release: 0.6.1 by @​younesbelkada in huggingface/peft#1103
• set dev version by @​younesbelkada in huggingface/peft#1104
• avoid unnecessary import by @​winglian in huggingface/peft#1109
• Refactor adapter deletion by @​BenjaminBossan in huggingface/peft#1105
• Added num_dataloader_workers arg to fix Windows issue by @​lukaskuhn-lku in huggingface/peft#1107
• Fix import issue transformers with id_tensor_storage by @​younesbelkada in huggingface/peft#1116
• Correctly deal with ModulesToSaveWrapper when using Low-level API by @​younesbelkada in huggingface/peft#1112
• fix doc typo by @​coding-famer in huggingface/peft#1121
• Release: v0.6.2 by @​pacman100 in huggingface/peft#1125
• Release: v0.6.3.dev0 by @​pacman100 in huggingface/peft#1128
• FIX: Adding 2 adapters when target_modules is a str fails by @​BenjaminBossan in huggingface/peft#1111

... (truncated)

Commits

• 2665f80 Release: 0.7.0 (#1214)
• 9fd788b TST: Add regression tests 2 (#1115)
• 2336780 Raise error when modules_to_save is specified and multiple adapters are bei...
• c22a8e5 DOC: How to configure new transformers models (#1195)
• 1a7433b TST Improve test for SD LoHa and OFT (#1210)
• 70d559d DOC Initialization options for LoRA (#1218)
• bffbbbf MNT Delete the delete doc workflows (#1213)
• 9c70468 [docs] API docs (#1196)
• f7cf460 [docs] Update index and quicktour (#1191)
• 1b1091c remove HF tokens (#1207)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot merge will merge this PR after your CI passes on it
• @dependabot squash and merge will squash and merge this PR after your CI passes on it
• @dependabot cancel merge will cancel a previously requested merge and block automerging
• @dependabot reopen will reopen this PR if it is closed
• @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
• @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)