mradermacher/CHIMERA-4B-RL-GGUF overview

---

base_model: TianHongZXY/CHIMERA-4B-RL

datasets:

• TianHongZXY/CHIMERA

language:

• en

library_name: transformers

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

• reasoning
• synthetic-data
• chain-of-thought

---

About

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static quants of https://huggingface.co/TianHongZXY/CHIMERA-4B-RL

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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/CHIMERA-4B-RL-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 |

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

| GGUF | Q2_K | 1.9 | |

| GGUF | Q3_K_S | 2.2 | |

| GGUF | Q3_K_M | 2.3 | lower quality |

| GGUF | Q3_K_L | 2.5 | |

| GGUF | IQ4_XS | 2.6 | |

| GGUF | Q4_K_S | 2.7 | fast, recommended |

| GGUF | Q4_K_M | 2.8 | fast, recommended |

| GGUF | Q5_K_S | 3.2 | |

| GGUF | Q5_K_M | 3.3 | |

| GGUF | Q6_K | 3.7 | very good quality |

| GGUF | Q8_0 | 4.8 | fast, best quality |

| GGUF | f16 | 8.9 | 16 bpw, overkill |

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.

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