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RichardErkhov/KoboldAI_-_LLaMA2-13B-Estopia-gguf
KoboldAI_-_LLaMA2-13B-Estopia-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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.gguf171 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
LLaMA2-13B-Estopia - GGUF
| Name | Quant method | Size |
|---|---|---|
| LLaMA2-13B-Estopia.Q2_K.gguf | Q2_K | 4.52GB |
| LLaMA2-13B-Estopia.IQ3_XS.gguf | IQ3_XS | 4.99GB |
| LLaMA2-13B-Estopia.IQ3_S.gguf | IQ3_S | 5.27GB |
| LLaMA2-13B-Estopia.Q3_K_S.gguf | Q3_K_S | 5.27GB |
| LLaMA2-13B-Estopia.IQ3_M.gguf | IQ3_M | 5.57GB |
| LLaMA2-13B-Estopia.Q3_K.gguf | Q3_K | 5.9GB |
| LLaMA2-13B-Estopia.Q3_K_M.gguf | Q3_K_M | 5.9GB |
| LLaMA2-13B-Estopia.Q3_K_L.gguf | Q3_K_L | 6.45GB |
| LLaMA2-13B-Estopia.IQ4_XS.gguf | IQ4_XS | 6.54GB |
| LLaMA2-13B-Estopia.Q4_0.gguf | Q4_0 | 6.86GB |
| LLaMA2-13B-Estopia.IQ4_NL.gguf | IQ4_NL | 6.9GB |
| LLaMA2-13B-Estopia.Q4_K_S.gguf | Q4_K_S | 6.91GB |
| LLaMA2-13B-Estopia.Q4_K.gguf | Q4_K | 7.33GB |
| LLaMA2-13B-Estopia.Q4_K_M.gguf | Q4_K_M | 7.33GB |
| LLaMA2-13B-Estopia.Q4_1.gguf | Q4_1 | 7.61GB |
| LLaMA2-13B-Estopia.Q5_0.gguf | Q5_0 | 8.36GB |
| LLaMA2-13B-Estopia.Q5_K_S.gguf | Q5_K_S | 8.36GB |
| LLaMA2-13B-Estopia.Q5_K.gguf | Q5_K | 8.6GB |
| LLaMA2-13B-Estopia.Q5_K_M.gguf | Q5_K_M | 8.6GB |
| LLaMA2-13B-Estopia.Q5_1.gguf | Q5_1 | 9.1GB |
| LLaMA2-13B-Estopia.Q6_K.gguf | Q6_K | 9.95GB |
| LLaMA2-13B-Estopia.Q8_0.gguf | Q8_0 | 12.88GB |
base_model:
\n### Instruction:\nWhat colour is the sky?\n### Response:\nThe sky is...<Story text>\n***\nWrite a summary of the text above\n***\nThe story starts by...User:Hello there!\nAssistant:Good morning...\n##||$||---||$||ASSISTANT:||$||[End||$||</s> - A single string for Kobold Lite combining the ones below##---ASSISTANT:[End</s>This model was made in three stages, along with many experimental stages which will be skipped for brevity. The first was internally referred to as EstopiaV9, which has a high degree of instruction following and creativity in responses, though they were generally shorter and a little more restricted in the scope of outputs, but conveyed nuance better.
merge_method: task_arithmetic
base_model: TheBloke/Llama-2-13B-fp16
models:
- model: TheBloke/Llama-2-13B-fp16
- model: Undi95/UtopiaXL-13B
parameters:
weight: 1.0
- model: Doctor-Shotgun/cat-v1.0-13b
parameters:
weight: 0.02
- model: PygmalionAI/mythalion-13b
parameters:
weight: 0.10
- model: Undi95/Emerhyst-13B
parameters:
weight: 0.05
- model: CalderaAI/13B-Thorns-l2
parameters:
weight: 0.05
- model: KoboldAI/LLaMA2-13B-Tiefighter
parameters:
weight: 0.20
dtype: float16
The second part of the merge was known as EstopiaV13. This produced responses which were long, but tended to write beyond good stopping points for further instructions to be added as it leant heavily on novel style prose. It did however benefit from a greater degree of neutrality as described above, and retained many of the detail tracking abilities of V9.
merge_method: task_arithmetic
base_model: TheBloke/Llama-2-13B-fp16
models:
- model: TheBloke/Llama-2-13B-fp16
- model: Undi95/UtopiaXL-13B
parameters:
weight: 1.0
- model: Doctor-Shotgun/cat-v1.0-13b
parameters:
weight: 0.01
- model: chargoddard/rpguild-chatml-13b
parameters:
weight: 0.02
- model: PygmalionAI/mythalion-13b
parameters:
weight: 0.08
- model: CalderaAI/13B-Thorns-l2
parameters:
weight: 0.02
- model: KoboldAI/LLaMA2-13B-Tiefighter
parameters:
weight: 0.20
dtype: float16
The third step was a merge between the two to retain the benefits of both as much as possible. This was performed using the dare merging technique.
# task-arithmetic style
models:
- model: EstopiaV9
parameters:
weight: 1
density: 1
- model: EstopiaV13
parameters:
weight: 0.05
density: 0.30
merge_method: dare_ties
base_model: TheBloke/Llama-2-13B-fp16
parameters:
int8_mask: true
dtype: bfloat16