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andrijdavid_-_Macaroni-v2-7b-gguf
RichardErkhov/andrijdavid_-_Macaroni-v2-7b-gguf
andrijdavid_-_Macaroni-v2-7b-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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82.2 GB
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.gguf95.2 GB · 100%
At a glance
- Access
- Public
- Created
- Aug 2, 2024
- Updated
- Aug 2, 2024
- SHA
- 57a8d8e8
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
Macaroni-v2-7b - GGUF
- Model creator: https://huggingface.co/andrijdavid/
- Original model: https://huggingface.co/andrijdavid/Macaroni-v2-7b/
| Name | Quant method | Size |
|---|---|---|
| Macaroni-v2-7b.Q2_K.gguf | Q2_K | 2.53GB |
| Macaroni-v2-7b.IQ3_XS.gguf | IQ3_XS | 2.81GB |
| Macaroni-v2-7b.IQ3_S.gguf | IQ3_S | 2.96GB |
| Macaroni-v2-7b.Q3_K_S.gguf | Q3_K_S | 2.95GB |
| Macaroni-v2-7b.IQ3_M.gguf | IQ3_M | 3.06GB |
| Macaroni-v2-7b.Q3_K.gguf | Q3_K | 3.28GB |
| Macaroni-v2-7b.Q3_K_M.gguf | Q3_K_M | 3.28GB |
| Macaroni-v2-7b.Q3_K_L.gguf | Q3_K_L | 3.56GB |
| Macaroni-v2-7b.IQ4_XS.gguf | IQ4_XS | 3.67GB |
| Macaroni-v2-7b.Q4_0.gguf | Q4_0 | 3.83GB |
| Macaroni-v2-7b.IQ4_NL.gguf | IQ4_NL | 3.87GB |
| Macaroni-v2-7b.Q4_K_S.gguf | Q4_K_S | 3.86GB |
| Macaroni-v2-7b.Q4_K.gguf | Q4_K | 4.07GB |
| Macaroni-v2-7b.Q4_K_M.gguf | Q4_K_M | 4.07GB |
| Macaroni-v2-7b.Q4_1.gguf | Q4_1 | 4.24GB |
| Macaroni-v2-7b.Q5_0.gguf | Q5_0 | 4.65GB |
| Macaroni-v2-7b.Q5_K_S.gguf | Q5_K_S | 4.65GB |
| Macaroni-v2-7b.Q5_K.gguf | Q5_K | 4.78GB |
| Macaroni-v2-7b.Q5_K_M.gguf | Q5_K_M | 4.78GB |
| Macaroni-v2-7b.Q5_1.gguf | Q5_1 | 5.07GB |
| Macaroni-v2-7b.Q6_K.gguf | Q6_K | 5.53GB |
| Macaroni-v2-7b.Q8_0.gguf | Q8_0 | 7.17GB |
Original model description:
base_model:
- flemmingmiguel/MBX-7B-v3
- mlabonne/OmniBeagle-7B
- mistralai/Mistral-7B-v0.1
- vanillaOVO/supermario_v4 tags:
- mergekit
- merge license: apache-2.0 language:
- en
Macaroni V2 7B
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the DARE TIES merge method using mistralai/Mistral-7B-v0.1 as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: mistralai/Mistral-7B-v0.1
# no parameters necessary for base model
- model: flemmingmiguel/MBX-7B-v3
parameters:
density: 0.7
weight: 0.5
- model: vanillaOVO/supermario_v4
parameters:
density: 0.7
weight: 0.3
- model: mlabonne/OmniBeagle-7B
parameters:
density: 0.5
weight: 0.6
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
int8_mask: true
normalize: true
dtype: float16
- Created
- Aug 2, 2024
- Updated
- Aug 2, 2024