What are the hardware requirements for SemAFacet SFT Merged 10K?

SemAFacet SFT Merged 10K requires approximately 4.9 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed SemAFacet SFT Merged 10K and how large is it?

SemAFacet SFT Merged 10K is developed by Neooooo, a model with 1.2b parameters. 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 SemAFacet SFT Merged 10K?

SemAFacet SFT Merged 10K is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SemAFacet SFT Merged 10K by Neooooo — VRAM 4.9GB, 128K context

Name: SemAFacet SFT Merged 10K
Author: Neooooo

SemAFacet SFT Merged 10K is an open-source language model by Neooooo. Features: 1.2b LLM, VRAM: 4.9GB, Context: 128K, Merged, LLM Explorer Score: 0.18.

Merged Model Arxiv:1910.09700 Conversational Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Neooooo/SemAFacet-SFT-Merged-10k

SemAFacet SFT Merged 10K Parameters and Internals

LLM Name	SemAFacet SFT Merged 10K
Repository 🤗	https://huggingface.co/Neooooo/SemAFacet-SFT-Merged-10k
Merged Model	Yes
Model Size	1.2b
Required VRAM	4.9 GB
Updated	2026-07-31
Maintainer	Neooooo
Model Type	llama
Model Files	2.0 GB: 1-of-3 1.9 GB: 2-of-3 1.0 GB: 3-of-3
Model Architecture	LlamaForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.51.3
Tokenizer Class	PreTrainedTokenizer
Vocabulary Size	128256
Torch Data Type	float32

Rank the SemAFacet SFT Merged 10K 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

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Mazgu Llama V3 Merged	128K / 2.5 GB	301	0
Assn2 Sft Train5	128K / 2.5 GB	7	0
Zay Llama1b DPO Harmful PathD	128K / 2.5 GB	1	1
Akshar Nano V2	128K / 2.5 GB	15	0
Akshar Nano	128K / 2.5 GB	10	0
Second Tts Try	128K / 2.5 GB	39	0
...18 27e6 491c B3ab Ea03a5b93541	128K / 4.9 GB	10	0
...e9 9a4a 4ead 84f4 71761ee932ca	128K / 4.9 GB	6	0
Llamainstructbadendings	128K / 2.5 GB	13	0
Llama Pubmed Example	128K / 2.5 GB	11	0

Note: green Score (e.g. "73.2") means that the model is better than Neooooo/SemAFacet-SFT-Merged-10k.