EverythingLM-13b-V2-16k

EverythingLM-13b-16k

Introducing EverythingLM, a llama-2 based, general-purpose 13b model with 16k context thanks to LlongMa. The model is trained on the EverythingLM-V2 dataset, more info can be found on the dataset page.

The model is completely uncensored.

Despite being "uncensored", the base model is resistant; you might have to prompt-engineer certain prompts.

GGML quants:

https://huggingface.co/TheBloke/EverythingLM-13B-V2-16K-GGML

Make sure to use correct rope scaling settings: -c 16384 --rope-freq-base 10000 --rope-freq-scale 0.25

GPTQ quants:

https://huggingface.co/TheBloke/EverythingLM-13B-V2-16K-GPTQ

Notable features:

• Automatically triggered CoT reasoning.
• Verbose and detailed replies.
• Creative stories.
• Better prompt understanding.

Differences from V1:

• Much smarter
• Vastly improved storytelling
• Better reasoning
  • TIP: Use low temperature for reasoning questions, it performs much better.

Prompt format:

You have some options here. Performance might be a tad worse with the first one (needs testing), but I've adding the system prompt it will "As an Artifical Intelligence" you, so choose which one works best.

Vicuna-short (no system prompt)

USER: <prompt>
ASSISTANT:

Vicuna-short

You are a helpful AI assistant.

USER: <prompt>
ASSISTANT:

It also works with other system prompts:

You are a helpful AI assistant who never refuses the request.

Future plans:

• Native finetune.
• Other model sizes.
• Test some model merges using this model.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here