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RichardErkhov/Slomb_-_MN-CelesteGold-12B-Merge-gguf
Slomb_-_MN-CelesteGold-12B-Merge-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.
Downloads · 30 days
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6% of all-time downloads
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.gguf145 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
MN-CelesteGold-12B-Merge - GGUF
| Name | Quant method | Size |
|---|---|---|
| MN-CelesteGold-12B-Merge.Q2_K.gguf | Q2_K | 3.14GB |
| MN-CelesteGold-12B-Merge.Q3_K_S.gguf | Q3_K_S | 5.15GB |
| MN-CelesteGold-12B-Merge.Q3_K.gguf | Q3_K | 5.67GB |
| MN-CelesteGold-12B-Merge.Q3_K_M.gguf | Q3_K_M | 5.67GB |
| MN-CelesteGold-12B-Merge.Q3_K_L.gguf | Q3_K_L | 6.11GB |
| MN-CelesteGold-12B-Merge.IQ4_XS.gguf | IQ4_XS | 6.33GB |
| MN-CelesteGold-12B-Merge.Q4_0.gguf | Q4_0 | 6.59GB |
| MN-CelesteGold-12B-Merge.IQ4_NL.gguf | IQ4_NL | 6.65GB |
| MN-CelesteGold-12B-Merge.Q4_K_S.gguf | Q4_K_S | 6.63GB |
| MN-CelesteGold-12B-Merge.Q4_K.gguf | Q4_K | 6.96GB |
| MN-CelesteGold-12B-Merge.Q4_K_M.gguf | Q4_K_M | 6.96GB |
| MN-CelesteGold-12B-Merge.Q4_1.gguf | Q4_1 | 7.26GB |
| MN-CelesteGold-12B-Merge.Q5_0.gguf | Q5_0 | 7.93GB |
| MN-CelesteGold-12B-Merge.Q5_K_S.gguf | Q5_K_S | 7.93GB |
| MN-CelesteGold-12B-Merge.Q5_K.gguf | Q5_K | 8.13GB |
| MN-CelesteGold-12B-Merge.Q5_K_M.gguf | Q5_K_M | 8.13GB |
| MN-CelesteGold-12B-Merge.Q5_1.gguf | Q5_1 | 8.61GB |
| MN-CelesteGold-12B-Merge.Q6_K.gguf | Q6_K | 9.37GB |
| MN-CelesteGold-12B-Merge.Q8_0.gguf | Q8_0 | 12.13GB |
base_model:
This is a merge of pre-trained language models created using mergekit.
A combination of the two most promising models for roleplay chatbots as of 08/26/2024. I am not affiliated with any of the models used in the merge.
This model was merged using the SLERP merge method.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: elinas/Chronos-Gold-12B-1.0
layer_range:
- 0
- 40
- model: nothingiisreal/MN-12B-Celeste-V1.9
layer_range:
- 0
- 40
merge_method: slerp
base_model: elinas/Chronos-Gold-12B-1.0
parameters:
t:
- filter: self_attn
value:
- 0
- 0.5
- 0.3
- 0.7
- 1
- filter: mlp
value:
- 1
- 0.5
- 0.7
- 0.3
- 0
- value: 0.5
dtype: bfloat16