mradermacher/ERNIE-4.5-300B-A47B-Base-PT-GGUF overview

---

base_model: baidu/ERNIE-4.5-300B-A47B-Base-PT

language:

• en
• zh

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

• ERNIE4.5

---

About

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static quants of https://huggingface.co/baidu/ERNIE-4.5-300B-A47B-Base-PT

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For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/ERNIE-4.5-300B-A47B-Base-PT-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's

READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for

more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

| Link | Type | Size/GB | Notes |

|:-----|:-----|--------:|:------|

| PART 1 PART 2 PART 3 | Q2_K | 109.2 | |

| PART 1 PART 2 PART 3 | Q3_K_S | 129.2 | |

| PART 1 PART 2 PART 3 | Q3_K_M | 142.7 | lower quality |

| PART 1 PART 2 PART 3 PART 4 | Q3_K_L | 155.2 | |

| PART 1 PART 2 PART 3 PART 4 | IQ4_XS | 160.6 | |

| PART 1 PART 2 PART 3 PART 4 | Q4_K_S | 169.7 | fast, recommended |

| PART 1 PART 2 PART 3 PART 4 | Q4_K_M | 180.3 | fast, recommended |

| P1 P2 P3 P4 P5 | Q5_K_S | 206.2 | |

| P1 P2 P3 P4 P5 | Q5_K_M | 212.1 | |

| P1 P2 P3 P4 P5 | Q6_K | 245.9 | very good quality |

| P1 P2 P3 P4 P5 P6 P7 | Q8_0 | 318.4 | fast, best quality |

Here is a handy graph by ikawrakow comparing some lower-quality quant

types (lower is better):

!image.png

And here are Artefact2's thoughts on the matter:

https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to

questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting

me use its servers and providing upgrades to my workstation to enable

this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

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