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---
base_model:
- nothingiisreal/L3.1-8B-Celeste-V1.5
- Sao10K/Llama-3.1-8B-Stheno-v3.4
- Sao10K/L3.1-8B-Niitama-v1.1
- arcee-ai/Llama-3.1-SuperNova-Lite
- akjindal53244/Llama-3.1-Storm-8B
- arcee-ai/Llama-Spark
- grimjim/Llama-3-Instruct-abliteration-LoRA-8B
- crestf411/sunfall-peft
tags:
- llama
- merge
- llama3
- mixtral
library_name: transformers
---
[](https://hf.co/QuantFactory)
# QuantFactory/L3.1-Celestial-Stone-2x8B-GGUF
This is quantized version of [v000000/L3.1-Celestial-Stone-2x8B](https://huggingface.co/v000000/L3.1-Celestial-Stone-2x8B) created using llama.cpp
# Original Model Card
> [!WARNING]
> **Content:**<br>
> This models output's can be a bit unhinged.
# Llama-3.1-Celestial-Stone-2x8B (BF16)
* *Mixture of Experts (14B).*
Both experts are used in tandem when generating a token.
------------------------------------------------------------------------------
* *Llama.CPP - GGUF.*
# Thank you mradermacher for the quants!
----> [GGUF iMatrix](https://huggingface.co/mradermacher/L3.1-Celestial-Stone-2x8B-i1-GGUF)
----> [GGUF static](https://huggingface.co/mradermacher/L3.1-Celestial-Stone-2x8B-GGUF)
Other alternative quants:
----> [Q8_0 GGUF by dasChronos1](https://huggingface.co/dasChronos1/L3.1-Celestial-Stone-2x8B-Q8_0-GGUF)
----> [Q6_K GGUF](https://huggingface.co/v000000/L3.1-Celestial-Stone-2x8B-Q6_K-GGUF)
----> [Q4_K_M GGUF by aashish1904](https://huggingface.co/aashish1904/L3.1-Celestial-Stone-2x8B-Q4_K_M-GGUF)
----> [Q2_K GGUF by aashish1904](https://huggingface.co/aashish1904/L3.1-Celestial-Stone-2x8B-Q2_K-GGUF)
------------------------------------------------------------------------------
*The first expert* is Instruct 405B distillation/RP vector merge <b>(Supernova-Lite, Niitama1.1, Storm)</b>
*The second expert* is ERP/Reddit data merge <b>(Celeste1.5, Stheno3.4, Storm)</b>
-------------------------------------------------------------------------------
*The base model* is <b>Sao10k/L3.1-Stheno-3.4</b> with the <b>Sunfall LoRa 0.6.1</b> to make it understand SillyTavern prompts and storywriting better.
-------------------------------------------------------------------------------
# Prompt Template:
```bash
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
{input}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
{output}<|eot_id|>
```
* *Other Details:*
*The model has 131072 context length, and is on Llama-3.1 and Mixtral architecture.*
*I did not abliterate the base model at all, so it will refuse zero-shot unethical questions. I recommend avoiding keywords like 'assistant, helpful, kind'*
# Recipe (I'm sorry...):
```yaml
slices:
- sources:
- model: Sao10K/L3.1-8B-Niitama-v1.1+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
layer_range: [0, 32]
- model: akjindal53244/Llama-3.1-Storm-8B
layer_range: [0, 32]
merge_method: nearswap
base_model: Sao10K/L3.1-8B-Niitama-v1.1+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
parameters:
t:
- value: 0.0001
dtype: bfloat16
out_type: float16
slices:
- sources:
- model: v000000/Llama-3.1-8B-Stheno-v3.4-abliterated
layer_range: [0, 32]
- model: akjindal53244/Llama-3.1-Storm-8B
layer_range: [0, 32]
merge_method: slerp
base_model: v000000/Llama-3.1-8B-Stheno-v3.4-abliterated
parameters:
t:
- filter: self_attn
value: [0.1, 0.6, 0.3, 0.8, 0.5]
- filter: mlp
value: [0.9, 0.4, 0.7, 0.2, 0.5]
- value: 0.5
dtype: float32
models:
- model: arcee-ai/Llama-3.1-SuperNova-Lite
parameters:
weight: 1.0
- model: v000000/L3.1-Niitorm-8B-t0.0001
parameters:
weight: 0.4
merge_method: task_arithmetic
base_model: arcee-ai/Llama-3.1-SuperNova-Lite
parameters:
normalize: false
dtype: float16
models:
- model: arcee-ai/Llama-3.1-SuperNova-Lite
parameters:
weight: 0.0
- model: v000000/L3.1-Niitorm-8B-t0.0001
parameters:
weight: 1.25
merge_method: task_arithmetic
base_model: arcee-ai/Llama-3.1-SuperNova-Lite
parameters:
normalize: false
dtype: float16
models:
- model: v000000/L3.1-8B-RP-Test-003-Task_Arithmetic
merge_method: slerp
base_model: v000000/L3.1-8B-RP-Test-002-Task_Arithmetic+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
parameters:
t:
- value: [0, 0, 0.3, 0.4, 0.5, 0.6, 0.5, 0.4, 0.3, 0, 0]
dtype: float16
base_model: nothingiisreal/L3.1-8B-Celeste-V1.5+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
dtype: bfloat16
merge_method: task_arithmetic
parameters:
normalize: false
slices:
- sources:
- layer_range: [0, 32]
model: nothingiisreal/L3.1-8B-Celeste-V1.5+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
parameters:
weight: 0.7
- layer_range: [0, 32]
model: v000000/L3.1-Sthenorm-8B
parameters:
weight: 0.2
- layer_range: [0, 32]
model: nothingiisreal/L3.1-8B-Celeste-V1.5
parameters:
weight: 0.2
base_model: crestf411/L3.1-8B-sunfall-stheno-v0.6.1
experts_per_token: 2
local_experts: 2
gate_mode: random
dtype: bfloat16
experts:
- source_model: v000000/L3.1-Storniitova-8B
- source_model: x0000001/l3.1-part_aaa
```
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