What are the hardware requirements for Relay Rssnnv Int8?

Relay Rssnnv Int8 requires approximately 0.1 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Relay Rssnnv Int8 and how large is it?

Relay Rssnnv Int8 is developed by joemia1993, a model with 80m 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 Relay Rssnnv Int8?

Relay Rssnnv Int8 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Relay Rssnnv Int8 by joemia1993 — VRAM 0.1GB, 32K context

Name: Relay Rssnnv Int8
Author: joemia1993

Relay Rssnnv Int8 is an open-source language model by joemia1993. Features: 80m LLM, VRAM: 0.1GB, Context: 32K, LLM Explorer Score: 0.28.

8-bit Bitsandbytes En Endpoints compatible Qwen2 Region:us Safetensors Zh

Model Card on HF 🤗: https://huggingface.co/joemia1993/relay-rssnnv-int8

Relay Rssnnv Int8 Parameters and Internals

LLM Name	Relay Rssnnv Int8
Repository 🤗	https://huggingface.co/joemia1993/relay-rssnnv-int8
Model Size	80m
Required VRAM	0.1 GB
Updated	2026-10-26
Maintainer	joemia1993
Model Type	qwen2
Model Files	0.1 GB
Supported Languages	en zh
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.44.2
Vocabulary Size	32000
Torch Data Type	bfloat16

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Instruction Following and Task Automation
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