Update README.md

README.md

@@ -10,3 +10,34 @@ license: mit
 
 <!-- Provide a quick summary of what the model is/does. -->
 This is an embedding model derived from [AutonLab/MOMENT-1-large](https://huggingface.co/AutonLab/MOMENT-1-large)
+
+## How to use
+```Python
+from transformers import AutoConfig, AutoModel, AutoFeatureExtractor
+
+model_name = "HachiML/MOMENT-1-large-embedding-v0.1"
+
+model = AutoModel.from_pretrained(model_name, trust_remote_code=True)
+feature_extractor = AutoFeatureExtractor.from_pretrained(model_name, trust_remote_code=True)
+```
+
+```Python
+import torch
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+print(device)
+
+model.to(device)
+```
+
+```Python
+hist_ndaq = pd.DataFrame("nasdaq_price_history.csv")
+input_data = hist_ndaq[["Open", "High", "Low", "Close", "Volume"]].iloc[:512]
+
+inputs = feature_extractor(input_data, return_tensors="pt")
+# inputs = feature_extractor([input_data], return_tensors="pt")  # You can also pass multiple data in a list.
+
+inputs = inputs.to(device)
+outputs = model(**inputs)
+print(outputs.embeddings)
+```