mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF overview
About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: static quants of https://huggingface.co/LocalAI io/LocalAI fu…
Runs locally from ~5.22 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| LocalAI-functioncall-phi-4-v0.2.IQ4_XS.gguf | GGUF | GGUF | 7.50 GB | Download |
| LocalAI-functioncall-phi-4-v0.2.Q2_K.gguf | GGUF | GGUF | 5.22 GB | Download |
| LocalAI-functioncall-phi-4-v0.2.Q3_K_L.gguf | GGUF | GGUF | 7.25 GB | Download |
| LocalAI-functioncall-phi-4-v0.2.Q3_K_M.gguf | GGUF | GGUF | 6.70 GB | Download |
| LocalAI-functioncall-phi-4-v0.2.Q3_K_S.gguf | GGUF | GGUF | 6.06 GB | Download |
| LocalAI-functioncall-phi-4-v0.2.Q4_K_M.gguf | GGUF | GGUF | 8.28 GB | Download |
| LocalAI-functioncall-phi-4-v0.2.Q4_K_S.gguf | GGUF | GGUF | 7.86 GB | Download |
| LocalAI-functioncall-phi-4-v0.2.Q5_K_M.gguf | GGUF | GGUF | 9.70 GB | Download |
| LocalAI-functioncall-phi-4-v0.2.Q5_K_S.gguf | GGUF | GGUF | 9.45 GB | Download |
| LocalAI-functioncall-phi-4-v0.2.Q6_K.gguf | GGUF | GGUF | 11.20 GB | Download |
| LocalAI-functioncall-phi-4-v0.2.Q8_0.gguf | GGUF | GGUF | 14.51 GB | Download |
Model Details
| Model ID | mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF |
|---|---|
| Author | mradermacher |
| Pipeline | — |
| License | apache-2.0 |
| Base model | LocalAI-io/LocalAI-functioncall-phi-4-v0.2 |
| Last modified | 2026-07-08T20:03:17.000Z |
Model README
---
base_model: LocalAI-io/LocalAI-functioncall-phi-4-v0.2
datasets:
- mudler/glaive-unsloth-localai
- mudler/o1-unsloth
- mlabonne/FineTome-100k
language:
- en
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
- sft
---
About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
static quants of https://huggingface.co/LocalAI-io/LocalAI-functioncall-phi-4-v0.2
<!-- provided-files -->
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-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 | 5.7 | |
| GGUF | Q3_K_S | 6.6 | |
| GGUF | Q3_K_M | 7.3 | lower quality |
| GGUF | Q3_K_L | 7.9 | |
| GGUF | IQ4_XS | 8.2 | |
| GGUF | Q4_K_S | 8.5 | fast, recommended |
| GGUF | Q4_K_M | 9.0 | fast, recommended |
| GGUF | Q5_K_S | 10.3 | |
| GGUF | Q5_K_M | 10.5 | |
| GGUF | Q6_K | 12.1 | very good quality |
| GGUF | Q8_0 | 15.7 | fast, best quality |
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.
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