first commit

docs/source/en/model_doc/timm_wrapper.md

@@ -0,0 +1,82 @@
+<!--Copyright 2024 The HuggingFace Team. All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
+an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
+specific language governing permissions and limitations under the License.
+
+⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
+rendered properly in your Markdown viewer.
+
+-->
+
+# TimmWrapper
+
+
+## Overview
+
+Helper class to enable loading timm models to be used with the transformers library and its autoclasses.
+
+```python
+from urllib.request import urlopen
+
+import torch
+from PIL import Image
+
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+
+
+# Load image
+image = Image.open(urlopen(
+    'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
+))
+
+# Load model and image processor
+checkpoint = "timm/resnet50.a1_in1k"
+image_processor = AutoImageProcessor.from_pretrained(checkpoint)
+model = AutoModelForImageClassification.from_pretrained(checkpoint).eval( device_map="auto")
+
+# Preprocess image
+inputs = image_processor(image)
+
+# Forward pass
+with torch.no_grad():
+    logits = model(**inputs).logits
+
+# Get top 5 predictions
+top5_probabilities, top5_class_indices = torch.topk(logits.softmax(dim=1) * 100, k=5)
+```
+
+## Resources
+
+A list of official Hugging Face and community (indicated by 🌎) resources to help you get started with TimmWrapper.
+
+<PipelineTag pipeline="image-classification"/>
+
+- [Collection of Example Notebook](https://github.com/ariG23498/timm-wrapper-examples) 🌎
+
+> [!TIP]
+> For a more detailed overview please read the [official blog post](https://huggingface.co/blog/timm-transformers) on the timm integration.
+
+## TimmWrapperConfig
+
+[[autodoc]] TimmWrapperConfig
+
+## TimmWrapperImageProcessor
+
+[[autodoc]] TimmWrapperImageProcessor
+    - preprocess
+
+## TimmWrapperModel
+
+[[autodoc]] TimmWrapperModel
+    - forward
+
+## TimmWrapperForImageClassification
+
+[[autodoc]] TimmWrapperForImageClassification
+    - forward