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picAIso_-_TARS-8B-gguf
RichardErkhov/picAIso_-_TARS-8B-gguf
picAIso_-_TARS-8B-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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92.9 GB
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.gguf108 GB · 100%
At a glance
- Access
- Public
- Created
- Aug 21, 2024
- Updated
- Aug 21, 2024
- SHA
- 111cdcc8
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
TARS-8B - GGUF
- Model creator: https://huggingface.co/picAIso/
- Original model: https://huggingface.co/picAIso/TARS-8B/
| Name | Quant method | Size |
|---|---|---|
| TARS-8B.Q2_K.gguf | Q2_K | 2.96GB |
| TARS-8B.IQ3_XS.gguf | IQ3_XS | 3.28GB |
| TARS-8B.IQ3_S.gguf | IQ3_S | 3.43GB |
| TARS-8B.Q3_K_S.gguf | Q3_K_S | 3.41GB |
| TARS-8B.IQ3_M.gguf | IQ3_M | 3.52GB |
| TARS-8B.Q3_K.gguf | Q3_K | 3.74GB |
| TARS-8B.Q3_K_M.gguf | Q3_K_M | 3.74GB |
| TARS-8B.Q3_K_L.gguf | Q3_K_L | 4.03GB |
| TARS-8B.IQ4_XS.gguf | IQ4_XS | 4.18GB |
| TARS-8B.Q4_0.gguf | Q4_0 | 4.34GB |
| TARS-8B.IQ4_NL.gguf | IQ4_NL | 4.38GB |
| TARS-8B.Q4_K_S.gguf | Q4_K_S | 4.37GB |
| TARS-8B.Q4_K.gguf | Q4_K | 4.58GB |
| TARS-8B.Q4_K_M.gguf | Q4_K_M | 4.58GB |
| TARS-8B.Q4_1.gguf | Q4_1 | 4.78GB |
| TARS-8B.Q5_0.gguf | Q5_0 | 5.21GB |
| TARS-8B.Q5_K_S.gguf | Q5_K_S | 5.21GB |
| TARS-8B.Q5_K.gguf | Q5_K | 5.34GB |
| TARS-8B.Q5_K_M.gguf | Q5_K_M | 5.34GB |
| TARS-8B.Q5_1.gguf | Q5_1 | 5.65GB |
| TARS-8B.Q6_K.gguf | Q6_K | 6.14GB |
| TARS-8B.Q8_0.gguf | Q8_0 | 7.95GB |
Original model description:
base_model:
- NousResearch/Hermes-2-Pro-Llama-3-8B
- nbeerbower/llama-3-gutenberg-8B
- MaziyarPanahi/Llama-3-8B-Instruct-v0.9 library_name: transformers tags:
- mergekit
- merge
- merging
- llama3
- merged license: llama3 language:
- en
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the TIES merge method using MaziyarPanahi/Llama-3-8B-Instruct-v0.9 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: MaziyarPanahi/Llama-3-8B-Instruct-v0.9
#no parameters necessary for base model
- model: NousResearch/Hermes-2-Pro-Llama-3-8B
parameters:
density: 0.5
weight: 0.8
- model: nbeerbower/llama-3-gutenberg-8B
parameters:
density: 0.5
weight: 0.8
merge_method: ties
base_model: MaziyarPanahi/Llama-3-8B-Instruct-v0.9
parameters:
normalize: false
int8_mask: true
dtype: float16
- Created
- Aug 21, 2024
- Updated
- Aug 21, 2024