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ABX-AI_-_Spicy-Laymonade-7B-gguf
RichardErkhov/ABX-AI_-_Spicy-Laymonade-7B-gguf
ABX-AI_-_Spicy-Laymonade-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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74.5 GB
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.gguf87.5 GB · 100%
At a glance
- Access
- Public
- Created
- May 1, 2024
- Updated
- May 1, 2024
- SHA
- 041a331b
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
Spicy-Laymonade-7B - GGUF
- Model creator: https://huggingface.co/ABX-AI/
- Original model: https://huggingface.co/ABX-AI/Spicy-Laymonade-7B/
| Name | Quant method | Size |
|---|---|---|
| Spicy-Laymonade-7B.Q2_K.gguf | Q2_K | 2.53GB |
| Spicy-Laymonade-7B.IQ3_XS.gguf | IQ3_XS | 2.81GB |
| Spicy-Laymonade-7B.IQ3_S.gguf | IQ3_S | 2.96GB |
| Spicy-Laymonade-7B.Q3_K_S.gguf | Q3_K_S | 2.95GB |
| Spicy-Laymonade-7B.IQ3_M.gguf | IQ3_M | 3.06GB |
| Spicy-Laymonade-7B.Q3_K.gguf | Q3_K | 3.28GB |
| Spicy-Laymonade-7B.Q3_K_M.gguf | Q3_K_M | 3.28GB |
| Spicy-Laymonade-7B.Q3_K_L.gguf | Q3_K_L | 3.56GB |
| Spicy-Laymonade-7B.IQ4_XS.gguf | IQ4_XS | 3.67GB |
| Spicy-Laymonade-7B.Q4_0.gguf | Q4_0 | 3.83GB |
| Spicy-Laymonade-7B.IQ4_NL.gguf | IQ4_NL | 3.87GB |
| Spicy-Laymonade-7B.Q4_K_S.gguf | Q4_K_S | 3.86GB |
| Spicy-Laymonade-7B.Q4_K.gguf | Q4_K | 4.07GB |
| Spicy-Laymonade-7B.Q4_K_M.gguf | Q4_K_M | 4.07GB |
| Spicy-Laymonade-7B.Q4_1.gguf | Q4_1 | 4.24GB |
| Spicy-Laymonade-7B.Q5_0.gguf | Q5_0 | 4.65GB |
| Spicy-Laymonade-7B.Q5_K_S.gguf | Q5_K_S | 4.65GB |
| Spicy-Laymonade-7B.Q5_K.gguf | Q5_K | 4.78GB |
| Spicy-Laymonade-7B.Q5_K_M.gguf | Q5_K_M | 4.78GB |
| Spicy-Laymonade-7B.Q5_1.gguf | Q5_1 | 5.07GB |
| Spicy-Laymonade-7B.Q6_K.gguf | Q6_K | 5.53GB |
Original model description:
base_model:
- cgato/TheSpice-7b-v0.1.1
- ABX-AI/Laymonade-7B library_name: transformers tags:
- mergekit
- merge
- not-for-all-audiences license: other
GGUF: https://huggingface.co/ABX-AI/Spicy-Laymonade-7B-GGUF-IQ-Imatrix
Spicy-Laymonade-7B
Well, we have Laymonade, so why not spice it up? This merge is a step into creating a new 9B.
However, I did try it out, and it seemed to work pretty well.
Merge Details
This is a merge of pre-trained language models created using mergekit.
Merge Method
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: cgato/TheSpice-7b-v0.1.1
layer_range: [0, 32]
- model: ABX-AI/Laymonade-7B
layer_range: [0, 32]
merge_method: slerp
base_model: ABX-AI/Laymonade-7B
parameters:
t:
- filter: self_attn
value: [0.7, 0.3, 0.6, 0.2, 0.5]
- filter: mlp
value: [0.3, 0.7, 0.4, 0.8, 0.5]
- value: 0.5
dtype: bfloat16
- Created
- May 1, 2024
- Updated
- May 1, 2024