# smol_llama-220M-GQA-32k-linear

Experimental model meant to serve as a long-context speculative decoding model.

Created using [BEE-spoke-data/smol_llama-220M-GQA](https://huggingface.co/BEE-spoke-data/smol_llama-220M-GQA) and further pretraining at 32768 context length on [togethercomputer/RedPajama-Data-1T-Sample](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T-Sample).

This variant uses the linear rope scaling method for context extension.

Wikitext Perplexity (64 rows) as evaluated by [exllamav2](https://github.com/turboderp/exllamav2):
```
Base Model
2048: 20.2193
4096: 102.6928
8192: 235.5210
16384: 390.7198
32768: 515.8053

32k - Linear Rope Scale 16.0
2048: 25.7148
4096: 23.4461
8192: 22.3326
16384: 21.6744
32768: 21.4317

32k - Rope Theta 1000000.0
2048: 20.2158
4096: 18.3868
8192: 17.5976
16384: 17.1462
32768: 16.6989
```
{"language": ["en"], "license": "apache-2.0", "tags": ["llama", "llama 2", "smol_llama"], "datasets": ["togethercomputer/RedPajama-Data-1T-Sample"]}
transformers pytorch llama text-generation llama 2 smol_llama en dataset:togethercomputer/RedPajama-Data-1T-Sample license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us