What are the hardware requirements for Shadowwork Shift Plain Sft?

Shadowwork Shift Plain Sft requires approximately 13.5 GB of VRAM and supports a context window of 488K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Shadowwork Shift Plain Sft and how large is it?

Shadowwork Shift Plain Sft is developed by i-am-shaurya05, a model with 3.3b 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 Shadowwork Shift Plain Sft?

Shadowwork Shift Plain Sft is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Shadowwork Shift Plain Sft by i-am-shaurya05 — VRAM 13.5GB, 488K context

Name: Shadowwork Shift Plain Sft
Author: i-am-shaurya05

Shadowwork Shift Plain Sft is an open-source language model by i-am-shaurya05. Features: 3.3b LLM, VRAM: 13.5GB, Context: 488K, License: cc-by-nc-4.0, LLM Explorer Score: 0.29.

Base model:coherelabs/tiny-aya... Base model:finetune:coherelabs... Cohere Cohere2 Conversational Endpoints compatible Lexsi Region:us Safetensors Shadowwork-shift Sharded Tensorflow Tiny-aya

Model Card on HF 🤗: https://huggingface.co/i-am-shaurya05/shadowwork-shift-plain-sft

Shadowwork Shift Plain Sft Parameters and Internals

LLM Name	Shadowwork Shift Plain Sft
Repository 🤗	https://huggingface.co/i-am-shaurya05/shadowwork-shift-plain-sft
Base Model(s)	CohereLabs/tiny-aya-global CohereLabs/tiny-aya-global
Model Size	3.3b
Required VRAM	13.5 GB
Updated	2026-11-13
Maintainer	i-am-shaurya05
Model Type	cohere2
Model Files	2.1 GB: 1-of-7 2.0 GB: 2-of-7 2.0 GB: 3-of-7 2.0 GB: 4-of-7 2.0 GB: 5-of-7 2.0 GB: 6-of-7 1.4 GB: 7-of-7
Model Architecture	Cohere2ForCausalLM
License	cc-by-nc-4.0
Context Length	500000
Model Max Length	500000
Transformers Version	5.17.0
Tokenizer Class	CohereTokenizer
Padding Token	<PAD>
Vocabulary Size	262144
Errors	replace

Rank the Shadowwork Shift Plain Sft 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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... Aya Global Esa Grpo Safe V3.1	8K / 6.7 GB	91	0
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Tiny Aya Global Hindi SFT	8K / 6.7 GB	46	0
...rth Langsafe Circuit Merge 0p5	8K / 6.7 GB	26	0
Lorde Tiny Aya	8K / 6.7 GB	25	0
... Aya 3.3B L2 Thinker BF16 GGUF	4882K / 6.7 GB	974	1

Note: green Score (e.g. "73.2") means that the model is better than i-am-shaurya05/shadowwork-shift-plain-sft.