What are the hardware requirements for Scm Phi3 Q4 K M V3?

Scm Phi3 Q4 K M V3 requires approximately 2.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Scm Phi3 Q4 K M V3 and how large is it?

Scm Phi3 Q4 K M V3 is developed by sebdg. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Scm Phi3 Q4 K M V3?

Scm Phi3 Q4 K M V3 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Scm Phi3 Q4 K M V3 by sebdg — VRAM 2.3GB

Name: Scm Phi3 Q4 K M V3
Author: sebdg

Scm Phi3 Q4 K M V3 is an open-source language model by sebdg. Features: LLM, VRAM: 2.3GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.13.

Base model:unsloth/phi-3-mini-... En Endpoints compatible Gguf Instruct License:apache-2.0 Mistral Q4 Quantized Region:us Tensorboard Unsloth

Model Card on HF 🤗: https://huggingface.co/sebdg/scm_phi3_q4_k_m_v3

Scm Phi3 Q4 K M V3 Parameters and Internals

LLM Name	Scm Phi3 Q4 K M V3
Repository 🤗	https://huggingface.co/sebdg/scm_phi3_q4_k_m_v3
Base Model(s)	Phi 3 Mini 4K Instruct unsloth/Phi-3-mini-4k-instruct
Required VRAM	2.3 GB
Updated	2024-07-15
Maintainer	sebdg
Model Type	mistral
Instruction-Based	Yes
Model Files	2.3 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf\|q4\|q4_k
Model Architecture	AutoModel
License	apache-2.0

Rank the Scm Phi3 Q4 K M V3 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Scm Phi3 Q4 K M V3

Best Alternatives	Context / RAM	Downloads	Likes
...ixtral 8x7B Instruct V0.1 GGUF	0K / 15.6 GB	18491	655
Dolphin 2.5 Mixtral 8x7b GGUF	0K / 15.6 GB	18101	314
Dolphin 2.7 Mixtral 8x7b GGUF	0K / 15.6 GB	12812	176
Phi 3 Mini 4K Instruct GGUF	0K / 1.4 GB	1429	17
Spydaz Web AI	0K / 4.4 GB	154	3
Autocomplete Model	0K / 4.1 GB	66	0
Dolphin 2 6 Phi 2 GGUF	0K / 1.2 GB	5273	75
Phi 3 Mini 4K Instruct	0K / 2.3 GB	22	0
...3 Mini 4k OLScience 4bitQ Gguf	0K / 2.3 GB	26	0
Dre Phi Gguf	0K / 2.3 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than sebdg/scm_phi3_q4_k_m_v3.