Sadjad Alikhani
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Update README.md
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README.md
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@@ -4,7 +4,7 @@ This repository contains the implementation of **LWM** (Large Wireless Model), a
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## How to Use
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###
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1. **Clone the Repository**
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preprocessed_chs = tokenizer(deepmimo_data, scenario_idxs, gen_raw=True)
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```
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5. **
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Choose the type of data you want to generate from the tokenized dataset, such as `cls_emb`, `channel_emb`, or `raw`:
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dataset = dataset_gen(preprocessed_chs, input_type, model)
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```
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Finally, you can use the generated raw channels and their inferred LWM embeddings in your downstream tasks:
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## How to Use
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### LWM Inference
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1. **Clone the Repository**
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preprocessed_chs = tokenizer(deepmimo_data, scenario_idxs, gen_raw=True)
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```
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5. **LWM Inference**
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Choose the type of data you want to generate from the tokenized dataset, such as `cls_emb`, `channel_emb`, or `raw`:
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dataset = dataset_gen(preprocessed_chs, input_type, model)
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```
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### Post-processing for Downstream Task
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1. **Use the Dataset in Downstream Tasks**
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Finally, you can use the generated raw channels and their inferred LWM embeddings in your downstream tasks:
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