Downloads · 30 days
0
gabrielbianchin/esm2_t33_long_int4
esm2_t33_long_int4 is a machine learning model from gabrielbianchin. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
ESM2 Quantized is an adapted version of the ESM2 architectures. It uses local attention instead of global attention, allowing for models with longer input sizes. ESM2 Quantized models have a context size of 2,050, dou…
Downloads · 30 days
0
Access
Public
Updated Aug 26, 2024
Repo size
16.3 MB
Likes
0
Public
Click a slice to open those files.
.safetensors16.3 MB · 100%
From the Hugging Face model README
ESM2 Quantized is an adapted version of the ESM2 architectures. It uses local attention instead of global attention, allowing for models with longer input sizes. ESM2 Quantized models have a context size of 2,050, double that of the standard ESM2 model. This kind of model was trained with int4 quantization. Several ESM2 Quantized models are available:
| Model | Num layers |
|---|---|
| gabrielbianchin/esm2_t36_long_int4 | 36 |
| gabrielbianchin/esm2_t33_long_int4 | 33 |
| gabrielbianchin/esm2_t30_long_int4 | 30 |
| gabrielbianchin/esm2_t12_long_int4 | 12 |
| gabrielbianchin/esm2_t6_long_int4 | 6 |
For detailed information, please refer to the paper.