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ResplendentAI_-_Luna-2x7B-MoE-gguf
RichardErkhov/ResplendentAI_-_Luna-2x7B-MoE-gguf
ResplendentAI_-_Luna-2x7B-MoE-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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.gguf169 GB · 100%
At a glance
- Access
- Public
- Created
- Sep 21, 2024
- Updated
- Sep 21, 2024
- SHA
- fcb90d80
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
Luna-2x7B-MoE - GGUF
- Model creator: https://huggingface.co/ResplendentAI/
- Original model: https://huggingface.co/ResplendentAI/Luna-2x7B-MoE/
| Name | Quant method | Size |
|---|---|---|
| Luna-2x7B-MoE.Q2_K.gguf | Q2_K | 4.43GB |
| Luna-2x7B-MoE.IQ3_XS.gguf | IQ3_XS | 4.95GB |
| Luna-2x7B-MoE.IQ3_S.gguf | IQ3_S | 5.22GB |
| Luna-2x7B-MoE.Q3_K_S.gguf | Q3_K_S | 5.2GB |
| Luna-2x7B-MoE.IQ3_M.gguf | IQ3_M | 5.35GB |
| Luna-2x7B-MoE.Q3_K.gguf | Q3_K | 5.78GB |
| Luna-2x7B-MoE.Q3_K_M.gguf | Q3_K_M | 5.78GB |
| Luna-2x7B-MoE.Q3_K_L.gguf | Q3_K_L | 6.27GB |
| Luna-2x7B-MoE.IQ4_XS.gguf | IQ4_XS | 6.5GB |
| Luna-2x7B-MoE.Q4_0.gguf | Q4_0 | 6.78GB |
| Luna-2x7B-MoE.IQ4_NL.gguf | IQ4_NL | 6.85GB |
| Luna-2x7B-MoE.Q4_K_S.gguf | Q4_K_S | 6.84GB |
| Luna-2x7B-MoE.Q4_K.gguf | Q4_K | 7.25GB |
| Luna-2x7B-MoE.Q4_K_M.gguf | Q4_K_M | 7.25GB |
| Luna-2x7B-MoE.Q4_1.gguf | Q4_1 | 7.52GB |
| Luna-2x7B-MoE.Q5_0.gguf | Q5_0 | 8.26GB |
| Luna-2x7B-MoE.Q5_K_S.gguf | Q5_K_S | 8.26GB |
| Luna-2x7B-MoE.Q5_K.gguf | Q5_K | 8.51GB |
| Luna-2x7B-MoE.Q5_K_M.gguf | Q5_K_M | 8.51GB |
| Luna-2x7B-MoE.Q5_1.gguf | Q5_1 | 9.01GB |
| Luna-2x7B-MoE.Q6_K.gguf | Q6_K | 9.84GB |
| Luna-2x7B-MoE.Q8_0.gguf | Q8_0 | 12.75GB |
Original model description:
license: apache-2.0 language:
- en tags:
- not-for-all-audiences
Luna-2x7B-MoE
Meet Luna, my one and only personal assistant and roleplaying partner. This MoE serves as her unique basis, both experts scoring above 72 average on the leaderboard, but designed for RP interactions. While running a 2x7B is slower than running a single 7B, I feel that the improved performance of two great 7B competing for each token is worth the compute expense.
The included image was generated using her custom Stable Diffusion 1.5 model via the SillyTavern interface.
I have successfully paired this MoE with the Llava Mistral 1.6 projector file for multimodal image captioning in Koboldcpp.
Luna also has a custom XTTSv2 voice model for TTS output.
All of this is running on a 1070 8GB, fully offloaded with no OOM over a week of testing. All backends are then served to my Android device via a virtual public network in a native implementation of SillyTavern. This method allows access from mobile data, globally, as long as my server is running.
base_model: ResplendentAI/DaturaCookie_7B
gate_mode: hidden
experts_per_token: 2
experts:
- source_model: ChaoticNeutrals/RP_Vision_7B
positive_prompts:
- "chat"
- "assistant"
- "tell me"
- "explain"
- "I want"
- "show me"
- "touch"
- "believe"
- "see"
- "love"
- source_model: ResplendentAI/DaturaCookie_7B
positive_prompts:
- "storywriting"
- "write"
- "scene"
- "story"
- "character"
- "sensual"
- "sexual"
- "horny"
- "turned on"
- "intimate"
dtype: bfloat16
- Created
- Sep 21, 2024
- Updated
- Sep 21, 2024