Update README.md

README.md

@@ -1,3 +1,36 @@
----
-license: mit
----
+---
+license: mit
+---
+
+OpenAI's GPT2-Small SAEs reformatted for easy loading from SAE Lens. 
+
+Links
+- [Paper](https://cdn.openai.com/papers/sparse-autoencoders.pdf)
+- [Original File Loading](https://github.com/openai/sparse_autoencoder/blob/lg-training/sparse_autoencoder/paths.py)
+
+```python
+import torch
+from transformer_lens import HookedTransformer
+from sae_lens import SAE, ActivationsStore
+
+torch.set_grad_enabled(False)
+model = HookedTransformer.from_pretrained("gpt2-small")
+sae, cfg, sparsity  = SAE.from_pretrained(
+  "gpt2-small-resid-post-v5-32k", # to see the list of available releases, go to: https://github.com/jbloomAus/SAELens/blob/main/sae_lens/pretrained_saes.yaml
+  "blocks.11.hook_resid_post" # change this to another specific SAE ID in the release if desired. 
+)
+
+# For loading activations or tokens from the training dataset.
+activation_store = ActivationsStore.from_sae(
+    model=model,
+    sae=sae,
+    streaming=True,
+    # fairly conservative parameters here so can use same for larger
+    # models without running out of memory.
+    store_batch_size_prompts=8,
+    train_batch_size_tokens=4096,
+    n_batches_in_buffer=4,
+    device=device,
+)
+
+```