From a recent PR by oobabooga:

This is what I get with 24gb vram (I haven’t tested extensively, it may be possible to go higher):

Model	Params	Maximum context
llama-13b	max_seq_len = 8192, compress_pos_emb = 4	6079 tokens
llama-30b	max_seq_len = 3584, compress_pos_emb = 2	3100 tokens

I also removed the chat_prompt_size parameter, since truncation_length can be reused for its purpose.

Now possible in text-generation-webui after this PR: https://github.com/oobabooga/text-generation-webui/pull/2875

I didn’t do anything other than exposing the compress_pos_emb parameter implemented by turboderp here, which in turn is based on kaiokendev’s recent discovery: https://kaiokendev.github.io/til#extending-context-to-8k

How to use it

• Open the Model tab, set the loader as ExLlama or ExLlama_HF.

• Set max_seq_len to a number greater than 2048. The length that you will be able to reach will depend on the model size and your GPU memory.

• Set compress_pos_emb to max_seq_len / 2048. For instance, use 2 for max_seq_len = 4096, or 4 for max_seq_len = 8192.

• Select the model that you want to load.

• Set truncation_length accordingly in the Parameters tab. You can set a higher default for this parameter by copying settings-template.yaml to settings.yaml in your text-generation-webui folder, and editing the values in settings.yaml.

• Those two new parameters can also be used from the command-line. For instance: python server.py --max_seq_len 4096 --compress_pos_emb 2. -