What are the hardware requirements for Temp Llada Instruct 30 Snr Weighted?

Temp Llada Instruct 30 Snr Weighted requires approximately 12.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Temp Llada Instruct 30 Snr Weighted and how large is it?

Temp Llada Instruct 30 Snr Weighted is developed by BashCache, a model with 8b 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 Temp Llada Instruct 30 Snr Weighted?

Temp Llada Instruct 30 Snr Weighted is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Temp Llada Instruct 30 Snr Weighted by BashCache — VRAM 12.4GB

Name: Temp Llada Instruct 30 Snr Weighted
Author: BashCache

Temp Llada Instruct 30 Snr Weighted is an open-source language model by BashCache. Features: 8b LLM, VRAM: 12.4GB, Instruction-Based, LLM Explorer Score: 0.28.

Custom code Instruct Llada Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/BashCache/temp-llada-instruct-30-snr-weighted

Temp Llada Instruct 30 Snr Weighted Parameters and Internals

LLM Name	Temp Llada Instruct 30 Snr Weighted
Repository 🤗	https://huggingface.co/BashCache/temp-llada-instruct-30-snr-weighted
Model Size	8b
Required VRAM	12.4 GB
Updated	2026-10-11
Maintainer	BashCache
Model Type	llada
Instruction-Based	Yes
Model Files	12.4 GB
Model Architecture	LLaDAModelLM
Transformers Version	4.47.1
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|endoftext\|>
Vocabulary Size	126464
Torch Data Type	bfloat16

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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

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