Update README.md

README.md

@@ -8,18 +8,22 @@ If you want to use them, do
 
 ```
 import torch
+from huggingface_hub import hf_hub_download
 
-def load_feat_acts(fname):
-  csr_kwargs = torch.load(fname)
+def load_feat_acts(fname, only_active_docs=False):
+  local_path = hf_hub_download(repo_id="noanabeshima/tiny_model_cached_acts", filename=fname)
+  csr_kwargs = torch.load(local_path)
 
   # The matrices are stored in space-efficient formats that're incompatible with torch's sparse csr tensor.
   # Convert them back before constructing the matrix.
   csr_kwargs['crow_indices'] = csr_kwargs['crow_indices'].int()
-  csr_kwargs['col_indices'] = csr_kwargs['crow_indices'].int()
-  csr_kwargs['values'] = csr_kwargs['values'].float()/255
+  csr_kwargs['col_indices'] = csr_kwargs['col_indices'].int()
+  csr_kwargs['values'] = (csr_kwargs['values'].float()/255)
   
   feat_acts = torch.sparse_csr_tensor(**csr_kwargs)
   return feat_acts
+
+feat_acts = load_feat_acts(f"mlp_map_test/M2_S-2_R1_P0/{300}.pt").to_dense()
 ```
 
 The activations are for the train split in https://huggingface.co/datasets/noanabeshima/TinyModelTokIds