What are the hardware requirements for Emhotob 500K V2?

Emhotob 500K V2 requires a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Emhotob 500K V2 and how large is it?

Emhotob 500K V2 is developed by oddadmix, a model with 518.2k 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 Emhotob 500K V2?

Emhotob 500K V2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Emhotob 500K V2 by oddadmix — 2K context

Name: Emhotob 500K V2
Author: oddadmix

Emhotob 500K V2 is an open-source language model by oddadmix. Features: 518.2k LLM, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.27.

Ar Arabic Dataset:kaust-generative-ai/fi... Emhotob Endpoints compatible From-scratch Llama Region:us Safetensors Small-language-model

Model Card on HF 🤗: https://huggingface.co/oddadmix/Emhotob-500K-v2

Emhotob 500K V2 Parameters and Internals

LLM Name	Emhotob 500K V2
Repository 🤗	https://huggingface.co/oddadmix/Emhotob-500K-v2
Model Size	518.2k
Required VRAM	0 GB
Updated	2026-08-08
Maintainer	oddadmix
Model Type	llama
Model Files	0.0 GB 0.0 GB
Supported Languages	ar
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	5.12.1
Tokenizer Class	TokenizersBackend
Padding Token	<pad>
Vocabulary Size	32000

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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 Emhotob 500K V2

Best Alternatives	Context / RAM	Downloads	Likes
Emhotob 500K	2K / 0 GB	9	0