Add model description and demo code

README.md

@@ -5,73 +5,36 @@ library_name: peft
 
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+This is an adapter for the Salesforce BLIP2 2.7B model (more information on the model [here](https://huggingface.co/Salesforce/blip2-opt-2.7b)). It was fine-tuned for generating product descriptions based on images using the [H&M dataset](https://www.kaggle.com/competitions/h-and-m-personalized-fashion-recommendations) from the kaggle challenge 2022.
 
 
+## How to Get Started with the Model
 
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### 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]
-
-## Bias, Risks, and Limitations
+Use the code below to get started with the model. Make sure to replace the path with a local path to an image.
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+```python
+from transformers import Blip2Processor, Blip2ForConditionalGeneration
+from PIL import Image
+import torch
 
-[More Information Needed]
+torch_dtype = torch.bfloat16
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-### Recommendations
+base_checkpoint = "Salesforce/blip2-opt-2.7b"
+base_model = Blip2ForConditionalGeneration.from_pretrained(base_checkpoint, torch_dtype=torch_dtype)
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+adapter_checkpoint = "CDL-RecSys/blip2-opt-2.7b-hm"
+model = PeftModel.from_pretrained(base_model, model_id=adapter_checkpoint)
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+processor = Blip2Processor.from_pretrained(base_checkpoint)
+tokenizer = processor.tokenizer
 
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
+image = Image.open("path/to/your/image.jpg")
+inputs = processor(image, return_tensors="pt").to(device, torch_dtype)
+generated_ids = model.generate(**inputs, max_length=max_length)
+generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)
+generated_text
+```
 
 ## Training Details