Downloads · 30 days
12
2% of all-time downloads
RichardErkhov/MrRobotoAI_-_Frejya-0.8b-gguf
MrRobotoAI_-_Frejya-0.8b-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.
Downloads · 30 days
12
2% of all-time downloads
All-time downloads
576
Public
Repo size
72.7 GB
Likes
0
Public
Click a slice to open those files.
.gguf85.7 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
Frejya-0.8b - GGUF
| Name | Quant method | Size |
|---|---|---|
| Frejya-0.8b.Q2_K.gguf | Q2_K | 2.53GB |
| Frejya-0.8b.Q3_K_S.gguf | Q3_K_S | 2.95GB |
| Frejya-0.8b.Q3_K.gguf | Q3_K | 3.28GB |
| Frejya-0.8b.Q3_K_M.gguf | Q3_K_M | 3.28GB |
| Frejya-0.8b.Q3_K_L.gguf | Q3_K_L | 3.56GB |
| Frejya-0.8b.IQ4_XS.gguf | IQ4_XS | 3.67GB |
| Frejya-0.8b.Q4_0.gguf | Q4_0 | 3.83GB |
| Frejya-0.8b.IQ4_NL.gguf | IQ4_NL | 3.87GB |
| Frejya-0.8b.Q4_K_S.gguf | Q4_K_S | 3.86GB |
| Frejya-0.8b.Q4_K.gguf | Q4_K | 4.07GB |
| Frejya-0.8b.Q4_K_M.gguf | Q4_K_M | 4.07GB |
| Frejya-0.8b.Q4_1.gguf | Q4_1 | 4.24GB |
| Frejya-0.8b.Q5_0.gguf | Q5_0 | 4.65GB |
| Frejya-0.8b.Q5_K_S.gguf | Q5_K_S | 4.65GB |
| Frejya-0.8b.Q5_K.gguf | Q5_K | 4.78GB |
| Frejya-0.8b.Q5_K_M.gguf | Q5_K_M | 4.78GB |
| Frejya-0.8b.Q5_1.gguf | Q5_1 | 5.07GB |
| Frejya-0.8b.Q6_K.gguf | Q6_K | 5.53GB |
| Frejya-0.8b.Q8_0.gguf | Q8_0 | 7.17GB |
base_model:
This is a merge of pre-trained language models created using mergekit.
This model was merged using the linear DARE merge method using OmnicromsBrain/Eros_Scribe-7b as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
models:
- model: MrRobotoAI/Loki-v5.2
parameters:
weight: 0.2
density: 0.9
- model: vaitech/open-hermes-sd-finetune-erot-story
parameters:
weight: 0.2
density: 0.9
- model: OmnicromsBrain/Eros_Scribe-7b
parameters:
weight: 0.2
density: 0.9
- model: MrRobotoAI/Hathor-v4.7
parameters:
weight: 0.2
density: 0.9
- model: OmnicromsBrain/TestmodelC
parameters:
weight: 0.2
density: 0.9
merge_method: dare_linear
base_model: OmnicromsBrain/Eros_Scribe-7b
parameters:
normalize: true
dtype: float16