Instructions to use chanind/gemma-2-2b-batch-topk-matryoshka-saes-w-32k-l0-40 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SAELens
How to use chanind/gemma-2-2b-batch-topk-matryoshka-saes-w-32k-l0-40 with SAELens:
# pip install sae-lens from sae_lens import SAE sae, cfg_dict, sparsity = SAE.from_pretrained( release = "RELEASE_ID", # e.g., "gpt2-small-res-jb". See other options in https://github.com/jbloomAus/SAELens/blob/main/sae_lens/pretrained_saes.yaml sae_id = "SAE_ID", # e.g., "blocks.8.hook_resid_pre". Won't always be a hook point ) - Notebooks
- Google Colab
- Kaggle
Upload SAE snap/blocks.9.hook_resid_post
Browse files
snap/blocks.9.hook_resid_post/cfg.json
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{"architecture": "jumprelu", "d_in": 2304, "d_sae": 32768, "dtype": "float32", "device": "cuda", "model_name": "gemma-2-2b", "hook_name": "blocks.9.hook_resid_post", "hook_layer": 9, "hook_head_index": null, "activation_fn_str": "relu", "activation_fn_kwargs": {"k": 40}, "apply_b_dec_to_input": true, "finetuning_scaling_factor": false, "sae_lens_training_version": "5.5.1", "prepend_bos": true, "dataset_path": "chanind/pile-uncopyrighted-gemma-1024-abbrv-1B", "dataset_trust_remote_code": true, "context_size": 1024, "normalize_activations": "none", "neuronpedia_id": null, "model_from_pretrained_kwargs": {"center_writing_weights": false}, "seqpos_slice": [null], "l1_coefficient": 0.001, "aux_coefficient": 0.03125, "lp_norm": 1.0, "use_ghost_grads": false, "normalize_sae_decoder": false, "noise_scale": 0.0, "decoder_orthogonal_init": false, "init_encoder_as_decoder_transpose": true, "mse_loss_normalization": null, "decoder_heuristic_init": true, "scale_sparsity_penalty_by_decoder_norm": false, "jumprelu_init_threshold": 0.001, "jumprelu_bandwidth": 0.001, "normalize_reconstruction_losses_by_d_in": false, "include_matryoshka_inner_l1_loss": false, "snapshot_checkpoint_path": null, "snap_start_step": 26157, "skip_outer_loss": true, "staged_training": false, "snap_reconstruction_loss": "L2", "snap_duration_steps": 15258, "outer_loss_multiplier": 1.0, "per_stage_k": null, "scale_snap_loss_factor": "auto", "snapshot_path": null, "matryoshka_inner_l1_loss_multipliers": 1.0, "matryoshka_reconstruction_loss": "MSE", "per_stage_l1_warmup_steps": null, "use_delta_loss": false, "use_matryoshka_aux_loss": true, "recalculate_scale_every_n_steps": 10, "per_stage_snap_start_step": 15258, "matryoshka_steps": [128, 512, 2048, 8192, 32768], "matryoshka_inner_loss_multipliers": 1.0, "scale_snap_for_full_stage": false, "include_bdec_loss": false, "normalize_losses_by_num_matryoshka_steps": true, "stage_duration_steps": 30517}
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snap/blocks.9.hook_resid_post/sae_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:4494aa3cd305e5a56920e87141d7fd1623d77fe8968d29d5989e4bea9ee38eaf
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size 604251536
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snap/blocks.9.hook_resid_post/sparsity.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ec517deda14cb7bc651688ab7c9edb992bf4099f892813c99385a1201c18e587
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size 131152
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