--- library_name: transformers tags: - mergekit - merge base_model: - Sao10K/L3-8B-Stheno-v3.2 - NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS - Hastagaras/Jamet-8B-L3-MK.V-Blackroot - nvidia/Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct - DavidAU/Llama-3.1-1million-ctx-Dark-Planet-8B ---

Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B

This repo contains the full precision source code, in "safe tensors" format to generate GGUFs, GPTQ, EXL2, AWQ, HQQ and other formats. The source code can also be used directly. "V1.01" has modifications to address some issues related to non-stop/overly long gen and/or repeat "end paragraph" issues. I am keeping the org quants too, because of the difference in creative generation between the two versions is very strong. I am not saying "reg" is better than "v1.01", they are just different, and you should have the choice between both in my opinion. The "GGUF" link at the bottom of the page links to repo with both V1.01 and "reg" quants in the repo. NOTE: If you intend to make GGUF quants, it is suggested to make the master file in float32 ("f32") then quant from this file due to float 32 components / models in this merge. (source files will be uploaded when parameter count shows in upper left) NOTE: Links to GGUFs below. IMPORTANT: Highest Quality Settings / Optimal Operation Guide / Parameters and Samplers If you are going to use this model, (source, GGUF or a different quant), please review this document for critical parameter, sampler and advance sampler settings (for multiple AI/LLM aps). This a "Class 3/4" (settings will enhance operation) model: For all settings used for this model (including specifics for its "class"), including example generation(s) and for advanced settings guide (which many times addresses any model issue(s)), including methods to improve model performance for all use case(s) as well as chat, roleplay and other use case(s) (especially for use case(s) beyond the model's design) please see: [ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ] REASON: Regardless of "model class" this document will detail methods to enhance operations. If the model is a Class 3/4 model the default settings (parameters, samplers, advanced samplers) must be set for "use case(s)" uses correctly. Some AI/LLM apps DO NOT have consistant default setting(s) which result in sub-par model operation. Like wise for Class 3/4 models (which operate somewhat to very differently than standard models) additional samplers and advanced samplers settings are required to "smooth out" operation, AND/OR also allow full operation for use cases the model was not designed for. BONUS - Use these settings for ANY model, ANY repo, ANY quant (including source/full precision): This document also details parameters, sampler and advanced samplers that can be use FOR ANY MODEL, FROM ANY REPO too - all quants, and of course source code operation too - to enhance the operation of any model. [ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ] NOTE: I strongly suggest you also visit the DavidAU GGUF (below) repo too for more details in using this model ; especially if it is "Class 3" or "Class 4" to get maximum performance from the model. For full information about this model, including: - Details about this model and its use case(s). - Context limits - Special usage notes / settings. - Any model(s) used to create this model. - Template(s) used to access/use this model. - Example generation(s) - GGUF quants of this model Please go to: [ https://huggingface.co/DavidAU/Llama-3.1-1-million-cxt-Dark-Planet-8B-GGUF ]