--- library_name: transformers tags: - not-for-all-audiences - axolotl - qlora language: - en license: other ---

MiS-Firefly-v0.2-22B

HF : FP16 | GGUF : Static GGUF

# Model Details **This is a fix for the quantization issue in Firefly v0.1.** Firefly is a Mistral Small 22B finetune designed for creative writing and roleplay. The model is largely uncensored and should support context up to 32,768 tokens. The model has been tested in various roleplay scenarios up to 16k context, as well as in a role as an assistant. It shows a broad competency & coherence across various scenarios. Special thanks to SicariusSicariiStuff for bouncing ideas back & forth on training, and SytanSD for quants. ## KNOWN QUANTIZATION ISSUE Some quants seem to have issues with misspelling complicated names. This doesn't happen at fp16 or q8_0 even with very weird names and multiple swipes meaning something's getting lost in quant. Suggested workarounds: - If you can, run q8_0 (I'm told this fits on a 4090 with flash attention), I haven't seen the issue in ~900 messages on q8. - If not, try some lower quants (ideally imatrix), I haven't tested them all but it appears to happen on Q6_K the most and less often on the 6.5bpw EXL2. If you find one where this doesn't happen, tell me. - If none of that works, use a simpler name. I'll try resolving it with a light merge ASAP, it seems like the wrong weight is just getting truncated in quantization causing these issues. # Feedback I appreciate all feedback on any of my models, you can use: * [My Discord server](https://discord.gg/AJwZuu7Ncx) - requires Discord. * [The Community tab](https://huggingface.co/invisietch/MiS-Firefly-v0.2-22B/discussions) - requires HF login. * Discord DMs to **invisietch**. Your feedback is how I improve these models for future versions. # Disclaimer This model is extensively uncensored. It can generate explicit, disturbing or offensive responses. Use responsibly. I am not responsible for your use of this model. This model is a finetune of Mistral Small 22B (2409) and usage must follow the terms of Mistral's license. By downloading this model, you agree not to use it for commercial purposes unless you have a valid Mistral commercial license. See [the base model card](https://huggingface.co/mistralai/Mistral-Small-Instruct-2409) for more details. # Prompting Format I'd recommend Mistral v2v3 prompting format: ``` ~~[INST] User message here.[/INST] Bot response here~~[INST] User message 2 here. ``` # Sampler Settings I'm running the following sampler settings but this is an RC and they may not be optimal. - **Temperature:** Dynamic 0.7-1.1 - **Min-P:** 0.07 - **Rep Pen:** 1.08 - **Rep Pen Range:** 1536 - **XTC:** 0.1/0.15 If you get completely incoherent responses, feel free to use these as a starting point. # Training Strategy I started with a finetune of Mistral Small 22B which had been trained on the Gutenberg dataset: [nbeerbower/Mistral-Small-Gutenberg-Doppel-22B](https://huggingface.co/nbeerbower/Mistral-Small-Gutenberg-Doppel-22B). The first stage of my training was a single epoch at low LR over a 474 million token text completion dataset. I followed this up with a coherence, decensorship & roleplay finetune over a 172 million token instruct dataset over two epochs. I did a slerp merge of epoch 1 into epoch 2 at a light weight which resolved the name-spelling issues on quantized versions of Firefly v0.1. Total training time was about 32hrs on 4x Nvidia A100 80GB.