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ContextPilot-E4B-i1-GGUF
mradermacher/ContextPilot-E4B-i1-GGUF
ContextPilot-E4B-i1-GGUF is a machine learning model from mradermacher. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as other.
weighted/imatrix quants of https://huggingface.co/tencent/ContextPilot-E4B
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At a glance
- Library
- transformers
- License
- other
- Access
- Public
- Created
- Aug 31, 2026
- Updated
- Aug 31, 2026
- SHA
- 9591a370
Base models
Model card
From the Hugging Face model README
About
<!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss --> <!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: -->weighted/imatrix quants of https://huggingface.co/tencent/ContextPilot-E4B
<!-- provided-files -->For a convenient overview and download list, visit our model page for this model.
static quants are available at https://huggingface.co/mradermacher/ContextPilot-E4B-GGUF
This is a vision model - mmproj files (if any) will be in the static repository.
Usage
If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs 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 | imatrix | 0.1 | imatrix file (for creating your own quants) |
| GGUF | i1-IQ1_S | 3.4 | for the desperate |
| GGUF | i1-IQ1_M | 3.5 | mostly desperate |
| GGUF | i1-IQ2_XXS | 3.6 | |
| GGUF | i1-IQ2_XS | 3.7 | |
| GGUF | i1-IQ2_S | 3.8 | |
| GGUF | i1-IQ2_M | 3.9 | |
| GGUF | i1-IQ3_XXS | 4.1 | lower quality |
| GGUF | i1-Q2_K_S | 4.4 | very low quality |
| GGUF | i1-Q2_K | 4.5 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XS | 4.6 | |
| GGUF | i1-Q3_K_S | 4.7 | IQ3_XS probably better |
| GGUF | i1-IQ3_S | 4.7 | beats Q3_K* |
| GGUF | i1-IQ3_M | 4.8 | |
| GGUF | i1-Q3_K_M | 4.9 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 5.1 | IQ3_M probably better |
| GGUF | i1-IQ4_XS | 5.1 | |
| GGUF | i1-IQ4_NL | 5.3 | prefer IQ4_XS |
| GGUF | i1-Q4_0 | 5.3 | fast, low quality |
| GGUF | i1-Q4_K_S | 5.3 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 5.4 | fast, recommended |
| GGUF | i1-Q4_1 | 5.5 | |
| GGUF | i1-Q5_K_S | 5.7 | |
| GGUF | i1-Q5_K_M | 5.8 | |
| GGUF | i1-Q6_K | 6.3 | practically like static Q6_K |
Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
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.
<!-- end -->- Library
- transformers
- License
- other
- Languages
- en
- Created
- Aug 31, 2026
- Updated
- Aug 31, 2026