Update README.md

README.md

@@ -1,12 +1,33 @@
 ---
 license: bsd-3-clause
-pipeline_tag: optical-flow-estimation
-tags:
-- model_hub_mixin
-- pytorch_model_hub_mixin
+language:
+- en
 ---
 
-This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
-- Code: [More Information Needed]
-- Paper: [More Information Needed]
-- Docs: [More Information Needed]
+# MEMFOF-Tartan-T-TSKH-spring
+
+<a href="" style="text-decoration: none;">📄 Paper</a> | <a href="https://msu-video-group.github.io/memfof" style="text-decoration: none;">🌐 Project Page</a> | <a href="https://github.com/msu-video-group/memfof" style="text-decoration: none;">💻 Code</a> | <a href="https://colab.research.google.com/github/msu-video-group/memfof/blob/dev/demo.ipynb" style="text-decoration: none;">🚀 Colab</a> | <a href="https://huggingface.co/spaces/egorchistov/MEMFOF" style="text-decoration: none;">🤗 Demo</a>
+
+🔍 This is a MEMFOF checkpoint trained **from MEMFOF-Tartan-T-TSKH** checkpoint on the **Spring** dataset.
+
+✅ **Note:** This model is intended for submission to **Spring benchmark**.
+
+## 🛠️ Usage
+
+```shell
+git clone https://github.com/msu-video-group/memfof.git
+cd memfof
+pip3 install -r requirements.txt
+```
+
+```python
+import torch
+from core.memfof import MEMFOF
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model = MEMFOF.from_pretrained("egorchistov/MEMFOF-Tartan-T-TSKH-spring").eval().to(device)
+
+with torch.inference_mode():
+    example_input = torch.randint(0, 256, [1, 3, 3, 1080, 1920], device=device)  # [B=1, T=3, C=3, H=1080, W=1920]
+    backward_flow, forward_flow = model(example_input).unbind(dim=1)  # [B=1, C=2, H=1080, W=1920]
+```