What are the hardware requirements for Slim Tags 3B?

Slim Tags 3B requires approximately 5.6 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Slim Tags 3B and how large is it?

Slim Tags 3B is developed by llmware, a model with 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 Slim Tags 3B?

Slim Tags 3B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Slim Tags 3B by llmware — VRAM 5.6GB, 4K context

Name: Slim Tags 3B
Author: llmware

Slim Tags 3B is an open-source language model by llmware. Features: 3b LLM, VRAM: 5.6GB, Context: 4K, License: cc-by-sa-4.0, LLM Explorer Score: 0.11.

Custom code Pytorch Region:us Stablelm epoch

Model Card on HF 🤗: https://huggingface.co/llmware/slim-tags-3b

Slim Tags 3B Parameters and Internals

Model Type

specialized function-calling model, tags classifier

Use Cases

Areas:

enhance search retrieval, categorization

Applications:

extract named entities, fact-checking, secondary validation for LLM outputs

Training Details

Methodology:

Fine-tuned on top of llmware/bling-stable-lm-3b-4e1t-v0

Input Output

Input Format:

function = 'classify' params = 'tags' prompt = ' ' + {text} + '\n' + '<{function}> ' + {params} + '' + '\n:'

Output Format:

Python dictionary with tags

LLM Name	Slim Tags 3B
Repository 🤗	https://huggingface.co/llmware/slim-tags-3b
Model Size	3b
Required VRAM	5.6 GB
Updated	2026-07-15
Maintainer	llmware
Model Type	stablelm_epoch
Model Files	5.6 GB
Model Architecture	StableLMEpochForCausalLM
License	cc-by-sa-4.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.33.2
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50304
Torch Data Type	bfloat16

Rank the Slim Tags 3B 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

Best Alternatives to Slim Tags 3B

Best Alternatives	Context / RAM	Downloads	Likes
Stable Code 3B Mlx	16K / 5.6 GB	17	1
Aura 3B	4K / 5.6 GB	3	2
Slim Extract	4K / 5.6 GB	10	13
Slim Boolean	4K / 5.6 GB	9	4
Slim Sa Ner	4K / 5.6 GB	20	6
Slim Summary	4K / 5.6 GB	10	8
Slim Xsum	4K / 5.6 GB	14	6
Tofu 3B	4K / 5.6 GB	5	2
Memphis CoT 3B	4K / 5.6 GB	24	31
Fett Uccine Mini 3B	4K / 5.6 GB	6	3

Note: green Score (e.g. "73.2") means that the model is better than llmware/slim-tags-3b.