Filter by type:
Filter by tags:
carnice-v2-27b
# Carnice-V2-27B for Hermes Agent
Carnice-V2-27B is a full merged BF16 SFT of `Qwen/Qwen3.6-27B` for Hermes-style agent traces. This repository contains the standalone merged model weights, not only a LoRA adapter.
## BF16 Transformers Loading Fix
The BF16 safetensors were republished with corrected `Qwen3_5ForConditionalGeneration` tensor prefixes. The original merge artifact accidentally serialized an extra Unsloth wrapper prefix, which caused direct HF Transformers loads to report the real weights as unexpected keys and initialize expected layers randomly. GGUF files were not affected because the GGUF conversion path normalized those prefixes.
## Benchmarks
The benchmark artifact bundle is included under `benchmarks/`. It contains the rendered graph, extracted `metrics.json`, benchmark scripts, and raw result files used to make the chart.
Scope note: the IFEval run is a short `limit=20` A/B smoke benchmark, not an official full leaderboard score. Held-out loss/perplexity is the exact assistant-only training-format validation metric from the SFT script. The raw BFCL two-case smoke files are included for auditability, but they are too small to use as a model-quality claim.
...
Repository: localaiLicense: apache-2.0
qwopus-glm-18b-merged
# 🪐 Qwen3.5-9B-GLM5.1-Distill-v1
## 📌 Model Overview
**Model Name:** `Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1`
**Base Model:** Qwen3.5-9B
**Training Type:** Supervised Fine-Tuning (SFT, Distillation)
**Parameter Scale:** 9B
**Training Framework:** Unsloth
This model is a distilled variant of **Qwen3.5-9B**, trained on high-quality reasoning data derived from **GLM-5.1**.
The primary goals are to:
- Improve **structured reasoning ability**
- Enhance **instruction-following consistency**
- Activate **latent knowledge via better reasoning structure**
## 📊 Training Data
### Main Dataset
- `Jackrong/GLM-5.1-Reasoning-1M-Cleaned`
- Cleaned from the original `Kassadin88/GLM-5.1-1000000x` dataset.
- Generated from a **GLM-5.1 teacher model**
- Approximately **700x** the scale of `Qwen3.5-reasoning-700x`
- Training used a **filtered subset**, not the full source dataset.
### Auxiliary Dataset
- `Jackrong/Qwen3.5-reasoning-700x`
...
Repository: localaiLicense: apache-2.0
qwopus-glm-18b-merged
# 🪐 Qwen3.5-9B-GLM5.1-Distill-v1
## 📌 Model Overview
**Model Name:** `Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1`
**Base Model:** Qwen3.5-9B
**Training Type:** Supervised Fine-Tuning (SFT, Distillation)
**Parameter Scale:** 9B
**Training Framework:** Unsloth
This model is a distilled variant of **Qwen3.5-9B**, trained on high-quality reasoning data derived from **GLM-5.1**.
The primary goals are to:
- Improve **structured reasoning ability**
- Enhance **instruction-following consistency**
- Activate **latent knowledge via better reasoning structure**
## 📊 Training Data
### Main Dataset
- `Jackrong/GLM-5.1-Reasoning-1M-Cleaned`
- Cleaned from the original `Kassadin88/GLM-5.1-1000000x` dataset.
- Generated from a **GLM-5.1 teacher model**
- Approximately **700x** the scale of `Qwen3.5-reasoning-700x`
- Training used a **filtered subset**, not the full source dataset.
### Auxiliary Dataset
- `Jackrong/Qwen3.5-reasoning-700x`
...
Repository: localaiLicense: apache-2.0
allura-org_q3-30b-a3b-pentiment
Triple stage RP/general tune of Qwen3-30B-A3b Base (finetune, merged for stablization, aligned)
Repository: localaiLicense: apache-2.0
nightwing3-10b-v0.1
Base model: (Falcon3-10B)
Repository: localaiLicense: falcon-llm
negative-anubis-70b-v1
Enjoyed SicariusSicariiStuff/Negative_LLAMA_70B but the prose was too dry for my tastes. So I merged it with TheDrummer/Anubis-70B-v1 for verbosity. Anubis has positivity bias so Negative could balance things out.
This is a merge of pre-trained language models created using mergekit.
The following models were included in the merge:
SicariusSicariiStuff/Negative_LLAMA_70B
TheDrummer/Anubis-70B-v1
Repository: localaiLicense: llama3.3
tarek07_legion-v2.1-llama-70b
My biggest merge yet, consisting of a total of 20 specially curated models. My methodology in approaching this was to create 5 highly specialized models:
A completely uncensored base A very intelligent model based on UGI, Willingness and NatInt scores on the UGI Leaderboard A highly descriptive writing model, specializing in creative and natural prose A RP model specially merged with fine-tuned models that use a lot of RP datasets The secret ingredient: A completely unhinged, uncensored final model
These five models went through a series of iterations until I got something I thought worked well and then combined them to make LEGION.
The full list of models used in this merge is below:
TheDrummer/Fallen-Llama-3.3-R1-70B-v1
Sao10K/Llama-3.3-70B-Vulpecula-r1
Sao10K/L3-70B-Euryale-v2.1
SicariusSicariiStuff/Negative_LLAMA_70B
allura-org/Bigger-Body-70b
Sao10K/70B-L3.3-mhnnn-x1
Sao10K/L3.3-70B-Euryale-v2.3
Doctor-Shotgun/L3.3-70B-Magnum-v4-SE
Sao10K/L3.1-70B-Hanami-x1
Sao10K/70B-L3.3-Cirrus-x1
EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
TheDrummer/Anubis-70B-v1
ArliAI/Llama-3.3-70B-ArliAI-RPMax-v1.4
LatitudeGames/Wayfarer-Large-70B-Llama-3.3
NeverSleep/Lumimaid-v0.2-70B
mlabonne/Hermes-3-Llama-3.1-70B-lorablated
ReadyArt/Forgotten-Safeword-70B-3.6
ReadyArt/Fallen-Abomination-70B-R1-v4.1
ReadyArt/Fallen-Safeword-70B-R1-v4.1
huihui-ai/Llama-3.3-70B-Instruct-abliterated
Repository: localaiLicense: llama3.3
steelskull_l3.3-shakudo-70b
L3.3-Shakudo-70b is the result of a multi-stage merging process by Steelskull, designed to create a powerful and creative roleplaying model with a unique flavor. The creation process involved several advanced merging techniques, including weight twisting, to achieve its distinct characteristics.
Stage 1: The Cognitive Foundation & Weight Twisting
The process began by creating a cognitive and tool-use focused base model, L3.3-Cogmoblated-70B. This was achieved through a `model_stock` merge of several models known for their reasoning and instruction-following capabilities. This base was built upon `nbeerbower/Llama-3.1-Nemotron-lorablated-70B`, a model intentionally "ablated" to skew refusal behaviors. This technique, known as weight twisting, helps the final model adopt more desirable response patterns by building upon a foundation that is already aligned against common refusal patterns.
Stage 2: The Twin Hydrargyrum - Flavor and Depth
Two distinct models were then created from the Cogmoblated base:
L3.3-M1-Hydrargyrum-70B: This model was merged using `SCE`, a technique that enhances creative writing and prose style, giving the model its unique "flavor." The Top_K for this merge were set at 0.22 .
L3.3-M2-Hydrargyrum-70B: This model was created using a `Della_Linear` merge, which focuses on integrating the "depth" of various roleplaying and narrative models. The settings for this merge were set at: (lambda: 1.1) (weight: 0.2) (density: 0.7) (epsilon: 0.2)
Final Stage: Shakudo
The final model, L3.3-Shakudo-70b, was created by merging the two Hydrargyrum variants using a 50/50 `nuslerp`. This final step combines the rich, creative prose (flavor) from the SCE merge with the strong roleplaying capabilities (depth) from the Della_Linear merge, resulting in a model with a distinct and refined narrative voice.
A special thank you to Nectar.ai for their generous support of the open-source community and my projects.
Additionally, a heartfelt thanks to all the Ko-fi supporters who have contributed—your generosity is deeply appreciated and helps keep this work going and the Pods spinning.
Repository: localaiLicense: llama3.3
meta-llama-3.1-8b-claude-imat
Meta-Llama-3.1-8B-Claude-iMat-GGUF: Quantized from Meta-Llama-3.1-8B-Claude fp16. Weighted quantizations were creating using fp16 GGUF and groups_merged.txt in 88 chunks and n_ctx=512. Static fp16 will also be included in repo. For a brief rundown of iMatrix quant performance, please see this PR. All quants are verified working prior to uploading to repo for your safety and convenience.
Repository: localaiLicense: llama3.1
llama-3.1-storm-8b-q4_k_m
We present the Llama-3.1-Storm-8B model that outperforms Meta AI's Llama-3.1-8B-Instruct and Hermes-3-Llama-3.1-8B models significantly across diverse benchmarks as shown in the performance comparison plot in the next section. Our approach consists of three key steps:
- Self-Curation: We applied two self-curation methods to select approximately 1 million high-quality examples from a pool of about 3 million open-source examples. Our curation criteria focused on educational value and difficulty level, using the same SLM for annotation instead of larger models (e.g. 70B, 405B).
- Targeted fine-tuning: We performed Spectrum-based targeted fine-tuning over the Llama-3.1-8B-Instruct model. The Spectrum method accelerates training by selectively targeting layer modules based on their signal-to-noise ratio (SNR), and freezing the remaining modules. In our work, 50% of layers are frozen.
- Model Merging: We merged our fine-tuned model with the Llama-Spark model using SLERP method. The merging method produces a blended model with characteristics smoothly interpolated from both parent models, ensuring the resultant model captures the essence of both its parents. Llama-3.1-Storm-8B improves Llama-3.1-8B-Instruct across 10 diverse benchmarks. These benchmarks cover areas such as instruction-following, knowledge-driven QA, reasoning, truthful answer generation, and function calling.
Repository: localaiLicense: llama3.1
kumiho-v1-rp-uwu-8b
Meet Kumiho-V1 uwu. Kumiho-V1-rp-UwU aims to be a generalist model with specialization in roleplay and writing capabilities. It is finetuned and merged with various models, with a heavy base of Meta's LLaMA 3.1-8B as base model, and Claude 3.5 Sonnet and Claude 3 Opus generated synthetic data.
Repository: localaiLicense: llama3.1
cathallama-70b
Notable Performance
9% overall success rate increase on MMLU-PRO over LLaMA 3.1 70b
Strong performance in MMLU-PRO categories overall
Great performance during manual testing
Creation workflow
Models merged
meta-llama/Meta-Llama-3.1-70B-Instruct
turboderp/Cat-Llama-3-70B-instruct
Nexusflow/Athene-70B
Repository: localaiLicense: llama3.1
llama3.1-bestmix-chem-einstein-8b
Llama3.1-BestMix-Chem-Einstein-8B is an innovative, meticulously blended model designed to excel in instruction-following, chemistry-focused tasks, and long-form conversational generation. This model fuses the best qualities of multiple Llama3-based architectures, making it highly versatile for both general and specialized tasks. 💻🧠✨
Repository: localaiLicense: apache-2.0
l3.1-8b-slush-i1
Slush is a two-stage model trained with high LoRA dropout, where stage 1 is a pretraining continuation on the base model, aimed at boosting the model's creativity and writing capabilities. This is then merged into the instruction tune model, and stage 2 is a fine tuning step on top of this to further enhance its roleplaying capabilities and/or to repair any damage caused in the stage 1 merge.
This is an initial experiment done on the at-this-point-infamous Llama 3.1 8B model, in an attempt to retain its smartness while addressing its abysmal lack of imagination/creativity. As always, feedback is welcome, and begone if you demand perfection.
The second stage, like the Sunfall series, follows the Silly Tavern preset, so ymmv in particular if you use some other tool and/or preset.
Repository: localaiLicense: llama3
dark-chivalry_v1.0-i1
The dark side of chivalry...
This model was merged using the TIES merge method using ValiantLabs/Llama3.1-8B-ShiningValiant2 as a base.
Repository: localaiLicense: apache-2.0
loki-v2.6-8b-1024k
The following models were included in the merge:
MrRobotoAI/Epic_Fiction-8b
MrRobotoAI/Unaligned-RP-Base-8b-1024k
MrRobotoAI/Loki-.Epic_Fiction.-8b
Casual-Autopsy/L3-Luna-8B
Casual-Autopsy/L3-Super-Nova-RP-8B
Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B
Casual-Autopsy/Halu-L3-Stheno-BlackOasis-8B
Undi95/Llama-3-LewdPlay-8B
Undi95/Llama-3-LewdPlay-8B-evo
Undi95/Llama-3-Unholy-8B
ChaoticNeutrals/Hathor_Tahsin-L3-8B-v0.9
ChaoticNeutrals/Hathor_RP-v.01-L3-8B
ChaoticNeutrals/Domain-Fusion-L3-8B
ChaoticNeutrals/T-900-8B
ChaoticNeutrals/Poppy_Porpoise-1.4-L3-8B
ChaoticNeutrals/Templar_v1_8B
ChaoticNeutrals/Hathor_Respawn-L3-8B-v0.8
ChaoticNeutrals/Sekhmet_Gimmel-L3.1-8B-v0.3
zeroblu3/LewdPoppy-8B-RP
tohur/natsumura-storytelling-rp-1.0-llama-3.1-8b
jeiku/Chaos_RP_l3_8B
tannedbum/L3-Nymeria-Maid-8B
Nekochu/Luminia-8B-RP
vicgalle/Humanish-Roleplay-Llama-3.1-8B
saishf/SOVLish-Maid-L3-8B
Dogge/llama-3-8B-instruct-Bluemoon-Freedom-RP
MrRobotoAI/Epic_Fiction-8b-v4
maldv/badger-lambda-0-llama-3-8b
maldv/llama-3-fantasy-writer-8b
maldv/badger-kappa-llama-3-8b
maldv/badger-mu-llama-3-8b
maldv/badger-lambda-llama-3-8b
maldv/badger-iota-llama-3-8b
maldv/badger-writer-llama-3-8b
Magpie-Align/MagpieLM-8B-Chat-v0.1
nbeerbower/llama-3-gutenberg-8B
nothingiisreal/L3-8B-Stheno-Horny-v3.3-32K
nbeerbower/llama-3-spicy-abliterated-stella-8B
Magpie-Align/MagpieLM-8B-SFT-v0.1
NeverSleep/Llama-3-Lumimaid-8B-v0.1
mlabonne/NeuralDaredevil-8B-abliterated
mlabonne/Daredevil-8B-abliterated
NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS
nothingiisreal/L3-8B-Instruct-Abliterated-DWP
openchat/openchat-3.6-8b-20240522
turboderp/llama3-turbcat-instruct-8b
UCLA-AGI/Llama-3-Instruct-8B-SPPO-Iter3
Undi95/Llama-3-LewdPlay-8B
TIGER-Lab/MAmmoTH2-8B-Plus
OwenArli/Awanllm-Llama-3-8B-Cumulus-v1.0
refuelai/Llama-3-Refueled
SicariusSicariiStuff/LLAMA-3_8B_Unaligned_Alpha
NousResearch/Hermes-2-Theta-Llama-3-8B
ResplendentAI/Nymph_8B
grimjim/Llama-3-Oasis-v1-OAS-8B
flammenai/Mahou-1.3b-llama3-8B
lemon07r/Llama-3-RedMagic4-8B
grimjim/Llama-3.1-SuperNova-Lite-lorabilterated-8B
grimjim/Llama-Nephilim-Metamorphosis-v2-8B
lemon07r/Lllama-3-RedElixir-8B
grimjim/Llama-3-Perky-Pat-Instruct-8B
ChaoticNeutrals/Hathor_RP-v.01-L3-8B
grimjim/llama-3-Nephilim-v2.1-8B
ChaoticNeutrals/Hathor_Respawn-L3-8B-v0.8
migtissera/Llama-3-8B-Synthia-v3.5
Locutusque/Llama-3-Hercules-5.0-8B
WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0
VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct
iRyanBell/ARC1-II
HPAI-BSC/Llama3-Aloe-8B-Alpha
HaitameLaf/Llama-3-8B-StoryGenerator
failspy/Meta-Llama-3-8B-Instruct-abliterated-v3
Undi95/Llama-3-Unholy-8B
ajibawa-2023/Uncensored-Frank-Llama-3-8B
ajibawa-2023/SlimOrca-Llama-3-8B
ChaoticNeutrals/Templar_v1_8B
aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K
ChaoticNeutrals/Hathor_Tahsin-L3-8B-v0.9
Blackroot/Llama-3-Gamma-Twist
FPHam/L3-8B-Everything-COT
Blackroot/Llama-3-LongStory
ChaoticNeutrals/Sekhmet_Gimmel-L3.1-8B-v0.3
abacusai/Llama-3-Smaug-8B
Khetterman/CursedMatrix-8B-v9
ajibawa-2023/Scarlett-Llama-3-8B-v1.0
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/physics_non_masked
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/electrical_engineering
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/college_chemistry
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/philosophy_non_masked
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/college_physics
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/philosophy
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/formal_logic
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/philosophy_100
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/conceptual_physics
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/college_computer_science
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/psychology_non_masked
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/psychology
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Blackroot/Llama3-RP-Lora
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/Llama-3-LimaRP-Instruct-LoRA-8B
MrRobotoAI/Unaligned-RP-Base-8b-1024k + nothingiisreal/llama3-8B-DWP-lora
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/world_religions
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/high_school_european_history
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/electrical_engineering
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/Llama-3-8B-Abomination-LORA
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/Llama-3-LongStory-LORA
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/human_sexuality
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/sociology
MrRobotoAI/Unaligned-RP-Base-8b-1024k + ResplendentAI/Theory_of_Mind_Llama3
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/Smarts_Llama3
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/Llama-3-LongStory-LORA
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/Nimue-8B
MrRobotoAI/Unaligned-RP-Base-8b-1024k + vincentyandex/lora_llama3_chunked_novel_bs128
MrRobotoAI/Unaligned-RP-Base-8b-1024k + ResplendentAI/Aura_Llama3
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/L3-Daybreak-8b-lora
MrRobotoAI/Unaligned-RP-Base-8b-1024k + ResplendentAI/Luna_Llama3
MrRobotoAI/Unaligned-RP-Base-8b-1024k + nicce/story-mixtral-8x7b-lora
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Blackroot/Llama-3-LongStory-LORA
MrRobotoAI/Unaligned-RP-Base-8b-1024k + ResplendentAI/NoWarning_Llama3
MrRobotoAI/Unaligned-RP-Base-8b-1024k + ResplendentAI/BlueMoon_Llama3
Repository: localaiLicense: llama3.1
tulu-3.1-8b-supernova-smart
This model was merged using the passthrough merge method using bunnycore/Tulu-3.1-8B-SuperNova + bunnycore/Llama-3.1-8b-smart-lora as a base.
Repository: localaiLicense: llama3.1
llmevollama-3.1-8b-v0.1-i1
This project aims to optimize model merging by integrating LLMs into evolutionary strategies in a novel way. Instead of using the CMA-ES approach, the goal is to improve model optimization by leveraging the search capabilities of LLMs to explore the parameter space more efficiently and adjust the search scope based on high-performing solutions.
Currently, the project supports optimization only within the Parameter Space, but I plan to extend its functionality to enable merging and optimization in the Data Flow Space as well. This will further enhance model merging by optimizing the interaction between data flow and parameters.
Repository: localaiLicense: llama3.1
ultravox-v0_5-llama-3_1-8b
Ultravox is a multimodal Speech LLM built around a pretrained Llama3.1-8B-Instruct and whisper-large-v3-turbo backbone.
See https://ultravox.ai for the GitHub repo and more information.
Ultravox is a multimodal model that can consume both speech and text as input (e.g., a text system prompt and voice user message). The input to the model is given as a text prompt with a special <|audio|> pseudo-token, and the model processor will replace this magic token with embeddings derived from the input audio. Using the merged embeddings as input, the model will then generate output text as usual.
In a future revision of Ultravox, we plan to expand the token vocabulary to support generation of semantic and acoustic audio tokens, which can then be fed to a vocoder to produce voice output. No preference tuning has been applied to this revision of the model.
Repository: localaiLicense: mit
wingless_imp_8b-i1
Highest rated 8B model according to a closed external benchmark. See details at the buttom of the page.
High IFeval for an 8B model that is not too censored: 74.30.
Strong Roleplay internet RP format lovers will appriciate it, medium size paragraphs (as requested by some people).
Very coherent in long context thanks to llama 3.1 models.
Lots of knowledge from all the merged models.
Very good writing from lots of books data and creative writing in late SFT stage.
Feels smart — the combination of high IFeval and the knowledge from the merged models show up.
Unique feel due to the merged models, no SFT was done to alter it, because I liked it as it is.
Repository: localaiLicense: llama3.1
ml-ms-etheris-123b
This model merges the robust storytelling of mutiple models while attempting to maintain intelligence. The final model was merged after Model Soup with DELLA to add some specal sause.
- model: NeverSleep/Lumimaid-v0.2-123B
- model: TheDrummer/Behemoth-123B-v1
- model: migtissera/Tess-3-Mistral-Large-2-123B
- model: anthracite-org/magnum-v2-123b
Use Mistral, ChatML, or Meth Format
Repository: localaiLicense: apache-2.0
Page 1