Downloads · 30 days
5
20% of all-time downloads
ss_d256_f1
jacobcd52/ss_d256_f1
ss_d256_f1 is a machine learning model from jacobcd52. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Weight-sparse transformer trained with the procedure from Gao et al. (2025).
All-time downloads
25
Public
Repo size
21 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin21 MB · 100%
At a glance
- Access
- Public
- Created
- Dec 14, 2025
- Updated
- Dec 14, 2025
- SHA
- c21c95e7
Model card
From the Hugging Face model README
ss_d256_f1
Weight-sparse transformer trained with the procedure from Gao et al. (2025).
Model Details
- Layers: 4
- Model Dimension: 256
- Context Length: 512
- Head Dimension: 16
- Vocabulary Size: 4096
Sparsity
- Weight Sparsity: False
- Target L0 Fraction: 1
- Activation Sparsity: False
Training
- Dataset: SimpleStories/SimpleStories
- Tokenizer: SimpleStories/SimpleStories-1.25M
- Total Tokens: 2,000,000,000
Training Run
Usage
import torch
from huggingface_hub import hf_hub_download
# Download model
model_path = hf_hub_download(repo_id="jacobcd52/ss_d256_f1", filename="pytorch_model.bin")
config_path = hf_hub_download(repo_id="jacobcd52/ss_d256_f1", filename="config.json")
# Load (requires the SparseGPT model class from this repo)
state_dict = torch.load(model_path)
- Created
- Dec 14, 2025
- Updated
- Dec 14, 2025