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RichardErkhov/bunnycore_-_Llama-3.2-3B-Prodigy-gguf
bunnycore_-_Llama-3.2-3B-Prodigy-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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.gguf44 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
Llama-3.2-3B-Prodigy - GGUF
| Name | Quant method | Size |
|---|---|---|
| Llama-3.2-3B-Prodigy.Q2_K.gguf | Q2_K | 1.39GB |
| Llama-3.2-3B-Prodigy.Q3_K_S.gguf | Q3_K_S | 1.59GB |
| Llama-3.2-3B-Prodigy.Q3_K.gguf | Q3_K | 1.73GB |
| Llama-3.2-3B-Prodigy.Q3_K_M.gguf | Q3_K_M | 1.73GB |
| Llama-3.2-3B-Prodigy.Q3_K_L.gguf | Q3_K_L | 1.85GB |
| Llama-3.2-3B-Prodigy.IQ4_XS.gguf | IQ4_XS | 1.91GB |
| Llama-3.2-3B-Prodigy.Q4_0.gguf | Q4_0 | 1.99GB |
| Llama-3.2-3B-Prodigy.IQ4_NL.gguf | IQ4_NL | 2.0GB |
| Llama-3.2-3B-Prodigy.Q4_K_S.gguf | Q4_K_S | 2.0GB |
| Llama-3.2-3B-Prodigy.Q4_K.gguf | Q4_K | 2.09GB |
| Llama-3.2-3B-Prodigy.Q4_K_M.gguf | Q4_K_M | 2.09GB |
| Llama-3.2-3B-Prodigy.Q4_1.gguf | Q4_1 | 2.18GB |
| Llama-3.2-3B-Prodigy.Q5_0.gguf | Q5_0 | 2.37GB |
| Llama-3.2-3B-Prodigy.Q5_K_S.gguf | Q5_K_S | 2.37GB |
| Llama-3.2-3B-Prodigy.Q5_K.gguf | Q5_K | 2.41GB |
| Llama-3.2-3B-Prodigy.Q5_K_M.gguf | Q5_K_M | 2.41GB |
| Llama-3.2-3B-Prodigy.Q5_1.gguf | Q5_1 | 2.55GB |
| Llama-3.2-3B-Prodigy.Q6_K.gguf | Q6_K | 2.76GB |
| Llama-3.2-3B-Prodigy.Q8_0.gguf | Q8_0 | 3.58GB |
base_model:
This is a merge of pre-trained language models created using mergekit.
This model was merged using the TIES merge method using huihui-ai/Llama-3.2-3B-Instruct-abliterated as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
models:
- model: bunnycore/Llama-3.2-3B-Sci-Think
parameters:
density: 0.5
weight: 0.5
- model: bunnycore/Llama-3.2-3B-Mix-Skill
parameters:
density: 0.5
weight: 0.5
- model: bunnycore/Llama-3.2-3B-Pure-RP
parameters:
density: 0.5
weight: 0.5
merge_method: ties
base_model: huihui-ai/Llama-3.2-3B-Instruct-abliterated
parameters:
normalize: false
int8_mask: true
dtype: float16