Update README.md

README.md

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 ## Model Details
 
-### Model Description
 
 <!-- Provide a longer summary of what this model is. -->
 
@@ -21,45 +20,32 @@ This is the model card of a 🤗 transformers model that has been pushed on the
 - **Funded by [optional]:** [More Information Needed]
 - **Shared by [optional]:** [More Information Needed]
 - **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
+- **Language(s) (NLP):** German
 - **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- **Finetuned from model [optional]:** [TrOCR_large_handwritten](https://huggingface.co/microsoft/trocr-large-handwritten)
 
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
 
 ## Uses
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
+Here is how to use this model in PyTorch:
+
+```python
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
+from PIL import Image
+import requests
+# load image from the IAM database
+url = 'https://fki.tic.heia-fr.ch/static/img/a01-122-02-00.jpg'
+image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
+processor = TrOCRProcessor.from_pretrained('TGrote11/testModel')
+model = VisionEncoderDecoderModel.from_pretrained('TGrote11/testModel')
+pixel_values = processor(images=image, return_tensors="pt").pixel_values
+generated_ids = model.generate(pixel_values)
+generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+```
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
+You can use the raw model for optical character recognition (OCR) on single text-line images of german handwriting.
 
 ### Recommendations