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RichardErkhov/tannedbum_-_Ellaria-9B-gguf
tannedbum_-_Ellaria-9B-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
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.gguf126 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
Ellaria-9B - GGUF
| Name | Quant method | Size |
|---|---|---|
| Ellaria-9B.Q2_K.gguf | Q2_K | 3.54GB |
| Ellaria-9B.IQ3_XS.gguf | IQ3_XS | 3.86GB |
| Ellaria-9B.IQ3_S.gguf | IQ3_S | 4.04GB |
| Ellaria-9B.Q3_K_S.gguf | Q3_K_S | 4.04GB |
| Ellaria-9B.IQ3_M.gguf | IQ3_M | 4.19GB |
| Ellaria-9B.Q3_K.gguf | Q3_K | 4.43GB |
| Ellaria-9B.Q3_K_M.gguf | Q3_K_M | 4.43GB |
| Ellaria-9B.Q3_K_L.gguf | Q3_K_L | 4.78GB |
| Ellaria-9B.IQ4_XS.gguf | IQ4_XS | 4.86GB |
| Ellaria-9B.Q4_0.gguf | Q4_0 | 5.07GB |
| Ellaria-9B.IQ4_NL.gguf | IQ4_NL | 5.1GB |
| Ellaria-9B.Q4_K_S.gguf | Q4_K_S | 5.1GB |
| Ellaria-9B.Q4_K.gguf | Q4_K | 5.37GB |
| Ellaria-9B.Q4_K_M.gguf | Q4_K_M | 5.37GB |
| Ellaria-9B.Q4_1.gguf | Q4_1 | 5.55GB |
| Ellaria-9B.Q5_0.gguf | Q5_0 | 6.04GB |
| Ellaria-9B.Q5_K_S.gguf | Q5_K_S | 6.04GB |
| Ellaria-9B.Q5_K.gguf | Q5_K | 6.19GB |
| Ellaria-9B.Q5_K_M.gguf | Q5_K_M | 6.19GB |
| Ellaria-9B.Q5_1.gguf | Q5_1 | 6.52GB |
| Ellaria-9B.Q6_K.gguf | Q6_K | 7.07GB |
| Ellaria-9B.Q8_0.gguf | Q8_0 | 9.15GB |
base_model:
Same reliable approach as before. A good RP model and a suitable dose of SimPO are a match made in heaven.
temp 0.9
top_k 30
top_p 0.75
min_p 0.2
rep_pen 1.1
smooth_factor 0.25
smooth_curve 1
Context & Instruct Presets for Gemma Here IMPORTANT !
Instruct Mode: Enabled
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: TheDrummer/Gemmasutra-9B-v1
layer_range: [0, 42]
- model: princeton-nlp/gemma-2-9b-it-SimPO
layer_range: [0, 42]
merge_method: slerp
base_model: TheDrummer/Gemmasutra-9B-v1
parameters:
t:
- filter: self_attn
value: [0.2, 0.4, 0.6, 0.2, 0.4]
- filter: mlp
value: [0.8, 0.6, 0.4, 0.8, 0.6]
- value: 0.4
dtype: bfloat16
Want to support my work ? My Ko-fi page: https://ko-fi.com/tannedbum