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vonPipe_-_jak2InstructSFT-gguf
RichardErkhov/vonPipe_-_jak2InstructSFT-gguf
vonPipe_-_jak2InstructSFT-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.
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807
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Repo size
92.9 GB
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.gguf108 GB · 100%
At a glance
- Access
- Public
- Created
- May 18, 2025
- Updated
- May 19, 2025
- SHA
- c13b7e72
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
jak2InstructSFT - GGUF
- Model creator: https://huggingface.co/vonPipe/
- Original model: https://huggingface.co/vonPipe/jak2InstructSFT/
| Name | Quant method | Size |
|---|---|---|
| jak2InstructSFT.Q2_K.gguf | Q2_K | 2.96GB |
| jak2InstructSFT.IQ3_XS.gguf | IQ3_XS | 3.28GB |
| jak2InstructSFT.IQ3_S.gguf | IQ3_S | 3.43GB |
| jak2InstructSFT.Q3_K_S.gguf | Q3_K_S | 3.41GB |
| jak2InstructSFT.IQ3_M.gguf | IQ3_M | 3.52GB |
| jak2InstructSFT.Q3_K.gguf | Q3_K | 3.74GB |
| jak2InstructSFT.Q3_K_M.gguf | Q3_K_M | 3.74GB |
| jak2InstructSFT.Q3_K_L.gguf | Q3_K_L | 4.03GB |
| jak2InstructSFT.IQ4_XS.gguf | IQ4_XS | 4.18GB |
| jak2InstructSFT.Q4_0.gguf | Q4_0 | 4.34GB |
| jak2InstructSFT.IQ4_NL.gguf | IQ4_NL | 4.38GB |
| jak2InstructSFT.Q4_K_S.gguf | Q4_K_S | 4.37GB |
| jak2InstructSFT.Q4_K.gguf | Q4_K | 4.58GB |
| jak2InstructSFT.Q4_K_M.gguf | Q4_K_M | 4.58GB |
| jak2InstructSFT.Q4_1.gguf | Q4_1 | 4.78GB |
| jak2InstructSFT.Q5_0.gguf | Q5_0 | 5.21GB |
| jak2InstructSFT.Q5_K_S.gguf | Q5_K_S | 5.21GB |
| jak2InstructSFT.Q5_K.gguf | Q5_K | 5.34GB |
| jak2InstructSFT.Q5_K_M.gguf | Q5_K_M | 5.34GB |
| jak2InstructSFT.Q5_1.gguf | Q5_1 | 5.65GB |
| jak2InstructSFT.Q6_K.gguf | Q6_K | 6.14GB |
| jak2InstructSFT.Q8_0.gguf | Q8_0 | 7.95GB |
Original model description:
base_model: vonPipe/selfiesPretrainInstruct tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
- sft license: apache-2.0 language:
- en
Uploaded model
- Developed by: vonPipe
- License: apache-2.0
- Finetuned from model : vonPipe/selfiesPretrainInstruct
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
- Created
- May 18, 2025
- Updated
- May 19, 2025