File size: 3,699 Bytes
f844bf7 3e104ee f844bf7 3e104ee f844bf7 3e104ee f844bf7 3e104ee 38a7805 4b676ea 38a7805 f844bf7 3e104ee f844bf7 3e104ee |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 |
---
language:
- sr
license: cc
tags:
- text-generation-inference
- transformers
- mistral
- gguf
zero base_model: gordicaleksa/YugoGPT
model_creator: Gordic Aleksa
model_type: mistral
quantized_by: datatab
datasets:
- datatab/alpaca-cleaned-serbian-full
---
# Yugo45-GPT-Quantized-GGUF
- **Quantized by:** datatab
- **License:** CC-BY-4.0
- **Original model author**: [gordicaleksa/YugoGPT](https://huggingface.co/gordicaleksa/YugoGPT/)
- **Special thanks for idea**: [**Stopwolf**](https://huggingface.co/Stopwolf) and this **X** post [**@TheStopwolf**](https://twitter.com/TheStopwolf/status/1761350502212599890)
<!-- description start -->
## Description
This repo contains GGUF format model files for [Yugo45-GPT](https://huggingface.co/datatab/Yugo45-GPT).
<!-- description end -->
# Quant. preference
| Quant. | Description |
|---------------|---------------------------------------------------------------------------------------|
| not_quantized | Recommended. Fast conversion. Slow inference, big files. |
| fast_quantized| Recommended. Fast conversion. OK inference, OK file size. |
| quantized | Recommended. Slow conversion. Fast inference, small files. |
| f32 | Not recommended. Retains 100% accuracy, but super slow and memory hungry. |
| f16 | Fastest conversion + retains 100% accuracy. Slow and memory hungry. |
| q8_0 | Fast conversion. High resource use, but generally acceptable. |
| q4_k_m | Recommended. Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q4_K |
| q5_k_m | Recommended. Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q5_K |
| q2_k | Uses Q4_K for the attention.vw and feed_forward.w2 tensors, Q2_K for the other tensors.|
| q3_k_l | Uses Q5_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K |
| q3_k_m | Uses Q4_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K |
| q3_k_s | Uses Q3_K for all tensors |
| q4_0 | Original quant method, 4-bit. |
| q4_1 | Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models.|
| q4_k_s | Uses Q4_K for all tensors |
| q4_k | alias for q4_k_m |
| q5_k | alias for q5_k_m |
| q5_0 | Higher accuracy, higher resource usage and slower inference. |
| q5_1 | Even higher accuracy, resource usage and slower inference. |
| q5_k_s | Uses Q5_K for all tensors |
| q6_k | Uses Q8_K for all tensors |
| iq2_xxs | 2.06 bpw quantization |
| iq2_xs | 2.31 bpw quantization |
| iq3_xxs | 3.06 bpw quantization |
| q3_k_xs | 3-bit extra small quantization | |