Downloads · 30 days
109
8% of all-time downloads
RichardErkhov/Gunulhona_-_Llama-Merge-Small-gguf
Gunulhona_-_Llama-Merge-Small-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
109
8% of all-time downloads
All-time downloads
1.4K
Public
Repo size
92.9 GB
Likes
0
Public
Click a slice to open those files.
.gguf108 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
Llama-Merge-Small - GGUF
| Name | Quant method | Size |
|---|---|---|
| Llama-Merge-Small.Q2_K.gguf | Q2_K | 2.96GB |
| Llama-Merge-Small.IQ3_XS.gguf | IQ3_XS | 3.28GB |
| Llama-Merge-Small.IQ3_S.gguf | IQ3_S | 3.43GB |
| Llama-Merge-Small.Q3_K_S.gguf | Q3_K_S | 3.41GB |
| Llama-Merge-Small.IQ3_M.gguf | IQ3_M | 3.52GB |
| Llama-Merge-Small.Q3_K.gguf | Q3_K | 3.74GB |
| Llama-Merge-Small.Q3_K_M.gguf | Q3_K_M | 3.74GB |
| Llama-Merge-Small.Q3_K_L.gguf | Q3_K_L | 4.03GB |
| Llama-Merge-Small.IQ4_XS.gguf | IQ4_XS | 4.18GB |
| Llama-Merge-Small.Q4_0.gguf | Q4_0 | 4.34GB |
| Llama-Merge-Small.IQ4_NL.gguf | IQ4_NL | 4.38GB |
| Llama-Merge-Small.Q4_K_S.gguf | Q4_K_S | 4.37GB |
| Llama-Merge-Small.Q4_K.gguf | Q4_K | 4.58GB |
| Llama-Merge-Small.Q4_K_M.gguf | Q4_K_M | 4.58GB |
| Llama-Merge-Small.Q4_1.gguf | Q4_1 | 4.78GB |
| Llama-Merge-Small.Q5_0.gguf | Q5_0 | 5.21GB |
| Llama-Merge-Small.Q5_K_S.gguf | Q5_K_S | 5.21GB |
| Llama-Merge-Small.Q5_K.gguf | Q5_K | 5.34GB |
| Llama-Merge-Small.Q5_K_M.gguf | Q5_K_M | 5.34GB |
| Llama-Merge-Small.Q5_1.gguf | Q5_1 | 5.65GB |
| Llama-Merge-Small.Q6_K.gguf | Q6_K | 6.14GB |
| Llama-Merge-Small.Q8_0.gguf | Q8_0 | 7.95GB |
base_model:
This is a merge of pre-trained language models created using mergekit.
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: meta-llama/Meta-Llama-3.1-8B-Instruct
layer_range: [0, 32]
- model: KISTI-KONI/KONI-Llama3-8B-Instruct-20240729
layer_range: [0, 32]
merge_method: slerp
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
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