Merge remote-tracking branch 'huggingface/main' into mayank/fp32-prompt-tuning

README.md

@@ -269,7 +269,7 @@ An example is provided in `~examples/causal_language_modeling/peft_lora_clm_acce
 | ViT           | ✅  |   |   |   | 
 | Swin           | ✅  |   |   |   | 
 
-___Note that we have tested LoRA for https://huggingface.co/docs/transformers/model_doc/vit and [https://huggingface.co/docs/transformers/model_doc/swin] for fine-tuning on image classification. However, it should be possible to use LoRA for any compatible model [provided](https://huggingface.co/models?pipeline_tag=image-classification&sort=downloads&search=vit) by 🤗 Transformers. Check out the respective
+___Note that we have tested LoRA for [ViT](https://huggingface.co/docs/transformers/model_doc/vit) and [Swin](https://huggingface.co/docs/transformers/model_doc/swin) for fine-tuning on image classification. However, it should be possible to use LoRA for any compatible model [provided](https://huggingface.co/models?pipeline_tag=image-classification&sort=downloads&search=vit) by 🤗 Transformers. Check out the respective
 examples to learn more. If you run into problems, please open an issue.___
 
 The same principle applies to our [segmentation models](https://huggingface.co/models?pipeline_tag=image-segmentation&sort=downloads) as well. 

setup.py

@@ -22,7 +22,7 @@ extras["dev"] = extras["quality"] + extras["docs_specific"]
 
 setup(
     name="peft",
-    version="0.1.0.dev0",
+    version="0.2.0.dev0",
     description="Parameter-Efficient Fine-Tuning (PEFT)",
     long_description=open("README.md", "r", encoding="utf-8").read(),
     long_description_content_type="text/markdown",

src/peft/__init__.py

@@ -17,7 +17,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__version__ = "0.1.0.dev0"
+__version__ = "0.2.0.dev0"
 
 from .mapping import MODEL_TYPE_TO_PEFT_MODEL_MAPPING, PEFT_TYPE_TO_CONFIG_MAPPING, get_peft_config, get_peft_model
 from .peft_model import (