Update README.md

README.md

@@ -1,3 +1,43 @@
----
-license: apache-2.0
----
+---
+license: mit
+---
+
+# Convert MUSE from TensorFlow to PyTorch and ONNX
+
+Read more about the project: [GitHub](https://github.com/dayyass/muse_tf2pt/tree/main).
+
+> [!IMPORTANT]
+> **The PyTorch model can be used not only for inference, but also for additional training and fine-tuning**.
+
+# Usage
+
+The model is available in [HF Models](https://huggingface.co/dayyass/universal-sentence-encoder-multilingual-large-3-pytorch/tree/main) directly through `torch` (*currently, without native support from the `transformers` library*).
+
+Model initialization and usage code:
+```python
+import torch
+from functools import partial
+from src.architecture import MUSE
+from src.tokenizer import get_tokenizer, tokenize
+
+PATH_TO_PT_MODEL = "model.pt"
+PATH_TO_TF_MODEL = "universal-sentence-encoder-multilingual-large-3"
+
+tokenizer = get_tokenizer(PATH_TO_TF_MODEL)
+tokenize = partial(tokenize, tokenizer=tokenizer)
+
+model_torch = MUSE(
+    num_embeddings=128010,
+    embedding_dim=512,
+    d_model=512,
+    num_heads=8,
+)
+model_torch.load_state_dict(
+    torch.load(PATH_TO_PT_MODEL)
+)
+
+sentence = "Hello, world!"
+res = model_torch(tokenize(sentence))
+```
+> [!NOTE]
+> Currently, the checkpoint of the original TF Hub model is used for tokenization, so it is loaded in the code above.