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PotatoB_-_evo_exp-point-1-3-gguf
RichardErkhov/PotatoB_-_evo_exp-point-1-3-gguf
PotatoB_-_evo_exp-point-1-3-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.
All-time downloads
466
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Repo size
82.2 GB
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0
Public
Repo makeup
Click a slice to open those files.
.gguf95.2 GB · 100%
At a glance
- Access
- Public
- Created
- Aug 9, 2024
- Updated
- Aug 9, 2024
- SHA
- 077a2c45
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
evo_exp-point-1-3 - GGUF
- Model creator: https://huggingface.co/PotatoB/
- Original model: https://huggingface.co/PotatoB/evo_exp-point-1-3/
| Name | Quant method | Size |
|---|---|---|
| evo_exp-point-1-3.Q2_K.gguf | Q2_K | 2.53GB |
| evo_exp-point-1-3.IQ3_XS.gguf | IQ3_XS | 2.81GB |
| evo_exp-point-1-3.IQ3_S.gguf | IQ3_S | 2.96GB |
| evo_exp-point-1-3.Q3_K_S.gguf | Q3_K_S | 2.95GB |
| evo_exp-point-1-3.IQ3_M.gguf | IQ3_M | 3.06GB |
| evo_exp-point-1-3.Q3_K.gguf | Q3_K | 3.28GB |
| evo_exp-point-1-3.Q3_K_M.gguf | Q3_K_M | 3.28GB |
| evo_exp-point-1-3.Q3_K_L.gguf | Q3_K_L | 3.56GB |
| evo_exp-point-1-3.IQ4_XS.gguf | IQ4_XS | 3.67GB |
| evo_exp-point-1-3.Q4_0.gguf | Q4_0 | 3.83GB |
| evo_exp-point-1-3.IQ4_NL.gguf | IQ4_NL | 3.87GB |
| evo_exp-point-1-3.Q4_K_S.gguf | Q4_K_S | 3.86GB |
| evo_exp-point-1-3.Q4_K.gguf | Q4_K | 4.07GB |
| evo_exp-point-1-3.Q4_K_M.gguf | Q4_K_M | 4.07GB |
| evo_exp-point-1-3.Q4_1.gguf | Q4_1 | 4.24GB |
| evo_exp-point-1-3.Q5_0.gguf | Q5_0 | 4.65GB |
| evo_exp-point-1-3.Q5_K_S.gguf | Q5_K_S | 4.65GB |
| evo_exp-point-1-3.Q5_K.gguf | Q5_K | 4.78GB |
| evo_exp-point-1-3.Q5_K_M.gguf | Q5_K_M | 4.78GB |
| evo_exp-point-1-3.Q5_1.gguf | Q5_1 | 5.07GB |
| evo_exp-point-1-3.Q6_K.gguf | Q6_K | 5.53GB |
| evo_exp-point-1-3.Q8_0.gguf | Q8_0 | 7.17GB |
Original model description:
license: apache-2.0 tags:
- merge
- mergekit
- lazymergekit
- meta-math/MetaMath-Mistral-7B
- openchat/openchat-3.5-1210
evo_exp-point-1-3
evo_exp-point-1-3 is a merge of the following models using mergekit:
🧩 Configuration
slices:
- sources:
- model: meta-math/MetaMath-Mistral-7B
layer_range: [0, 32]
- model: openchat/openchat-3.5-1210
layer_range: [0, 32]
merge_method: slerp
base_model: meta-math/MetaMath-Mistral-7B
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
- Created
- Aug 9, 2024
- Updated
- Aug 9, 2024