add(docs): Add detailed description and usage of Monkey V4 model to README

README.md

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 license: openrail
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+# Monkey V4 Data Driven + Attention Readout Model Card
+
+Neural Encoding model for Macaque V4. The model is a combination of a data driven core and an attention readout layer.
+
+## Model Details
+### Model Description
+
+This model is a combination of a data driven core and an attention readout layer.
+The data driven core is a convolutional neural network and the attention readout layer is a multihead attention layer with each head trained to predict the firing rates of a neuron in Macaque V4.
+
+### Model Sources
+For research purposes, we recommend our `nnvision` Github repository (https://github.com/sinzlab/nnvision), which contains the code for the model defintions and training.
+
+Repository: https://github.com/sinzlab/nnvision
+Paper: https://www.biorxiv.org/content/10.1101/2023.05.18.541176v1
+
+### Intended Use
+
+The model is intended for research purposes only.
+
+### Model Use
+
+The model can be used to predict the firing rates of neurons in Macaque V4 given an image.
+
+#### nnvision
+The model can be used in Python with the `nnvision` package.
+```python
+import torch
+from nnvision.models.trained_models.v4_data_driven import v4_multihead_attention_ensemble_model
+
+input_image = torch.rand(1, 100, 100)
+firing_rate = v4_multihead_attention_ensemble_model(input_image, data_key="all_sessions")
+```
+
+### energy-guided diffusion
+The model can be used in Python with the `energy-guided-diffusion` package.
+```python
+from egg.models import models
+model = models['data_driven']['train']
+```