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LocalAI-functioncall-phi-4-v0.1-i1-GGUF

Transformers
GGUF
English
text-generation-inference
unsloth
llama
trl
sft
Inference Endpoints
imatrix
conversational
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  <!-- ### quantize_version: 2 -->
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  <!-- ### output_tensor_quantised: 1 -->
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  <!-- ### convert_type: hf -->
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  <!-- ### vocab_type: -->
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  <!-- ### tags: nicoboss -->
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  weighted/imatrix quants of https://huggingface.co/mudler/LocalAI-functioncall-phi-4-v0.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ base_model: mudler/LocalAI-functioncall-phi-4-v0.1
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+ datasets:
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+ - mudler/glaive-unsloth-localai
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+ - mlabonne/FineTome-100k
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+ language:
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+ - en
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+ library_name: transformers
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+ license: apache-2.0
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+ quantized_by: mradermacher
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+ tags:
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+ - text-generation-inference
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+ - transformers
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+ - unsloth
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+ - llama
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+ - trl
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+ - sft
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+ ---
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+ ## About
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+
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  <!-- ### quantize_version: 2 -->
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  <!-- ### output_tensor_quantised: 1 -->
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  <!-- ### convert_type: hf -->
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  <!-- ### vocab_type: -->
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  <!-- ### tags: nicoboss -->
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  weighted/imatrix quants of https://huggingface.co/mudler/LocalAI-functioncall-phi-4-v0.1
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+
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+ <!-- provided-files -->
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+ static quants are available at https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-GGUF
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+ ## Usage
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+
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+ If you are unsure how to use GGUF files, refer to one of [TheBloke's
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+ READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
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+ more details, including on how to concatenate multi-part files.
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+
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+ ## Provided Quants
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+
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+ (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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+
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+ | Link | Type | Size/GB | Notes |
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+ |:-----|:-----|--------:|:------|
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-IQ1_S.gguf) | i1-IQ1_S | 3.5 | for the desperate |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-IQ1_M.gguf) | i1-IQ1_M | 3.8 | mostly desperate |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 4.3 | |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-IQ2_XS.gguf) | i1-IQ2_XS | 4.7 | |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-IQ2_S.gguf) | i1-IQ2_S | 4.9 | |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-IQ2_M.gguf) | i1-IQ2_M | 5.3 | |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-Q2_K_S.gguf) | i1-Q2_K_S | 5.3 | very low quality |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-Q2_K.gguf) | i1-Q2_K | 5.7 | IQ3_XXS probably better |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 5.9 | lower quality |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-IQ3_XS.gguf) | i1-IQ3_XS | 6.3 | |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-Q3_K_S.gguf) | i1-Q3_K_S | 6.6 | IQ3_XS probably better |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-IQ3_S.gguf) | i1-IQ3_S | 6.6 | beats Q3_K* |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-IQ3_M.gguf) | i1-IQ3_M | 6.8 | |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-Q3_K_M.gguf) | i1-Q3_K_M | 7.3 | IQ3_S probably better |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-Q3_K_L.gguf) | i1-Q3_K_L | 7.9 | IQ3_M probably better |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-IQ4_XS.gguf) | i1-IQ4_XS | 8.1 | |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-Q4_0.gguf) | i1-Q4_0 | 8.5 | fast, low quality |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-IQ4_NL.gguf) | i1-IQ4_NL | 8.5 | prefer IQ4_XS |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-Q4_K_S.gguf) | i1-Q4_K_S | 8.5 | optimal size/speed/quality |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-Q4_K_M.gguf) | i1-Q4_K_M | 9.0 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-Q4_1.gguf) | i1-Q4_1 | 9.4 | |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-Q5_K_S.gguf) | i1-Q5_K_S | 10.3 | |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-Q5_K_M.gguf) | i1-Q5_K_M | 10.5 | |
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+ | [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.1-i1-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.1.i1-Q6_K.gguf) | i1-Q6_K | 12.1 | practically like static Q6_K |
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+
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+ Here is a handy graph by ikawrakow comparing some lower-quality quant
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+ types (lower is better):
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+
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+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
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+
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+ And here are Artefact2's thoughts on the matter:
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+ https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
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+
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+ ## FAQ / Model Request
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+
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+ See https://huggingface.co/mradermacher/model_requests for some answers to
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+ questions you might have and/or if you want some other model quantized.
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+
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+ ## Thanks
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+
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+ I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
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+ me use its servers and providing upgrades to my workstation to enable
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+ this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/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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+
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+ <!-- end -->