What are the hardware requirements for SmollerLM 20M Instruct Pruned Sft5?

SmollerLM 20M Instruct Pruned Sft5 requires approximately 0.1 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed SmollerLM 20M Instruct Pruned Sft5 and how large is it?

SmollerLM 20M Instruct Pruned Sft5 is developed by mehmetkeremturkcan, a model with 20m 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 SmollerLM 20M Instruct Pruned Sft5?

SmollerLM 20M Instruct Pruned Sft5 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SmollerLM 20M Instruct Pruned Sft5 by mehmetkeremturkcan — VRAM 0.1GB, 8K context

Name: SmollerLM 20M Instruct Pruned Sft5
Author: mehmetkeremturkcan

SmollerLM 20M Instruct Pruned Sft5 is an open-source language model by mehmetkeremturkcan. Features: 20m LLM, VRAM: 0.1GB, Context: 8K, Instruction-Based, LLM Explorer Score: 0.16.

Base model:finetune:mehmetkere... Base model:mehmetkeremturkcan/... Conversational Dataset:huggingfacetb/smol-smo... Endpoints compatible Generated from trainer Instruct Llama Region:us Safetensors Sft Tensorboard Trl

Model Card on HF 🤗: https://huggingface.co/mehmetkeremturkcan/SmollerLM-20M-Instruct-Pruned-sft5

SmollerLM 20M Instruct Pruned Sft5 Parameters and Internals

LLM Name	SmollerLM 20M Instruct Pruned Sft5
Repository 🤗	https://huggingface.co/mehmetkeremturkcan/SmollerLM-20M-Instruct-Pruned-sft5
Model Name	SmollerLM-20M-Instruct-Pruned-sft5
Base Model(s)	mehmetkeremturkcan/SmollerLM-20M-Instruct-Pruned-Base mehmetkeremturkcan/SmollerLM-20M-Instruct-Pruned-Base
Model Size	20m
Required VRAM	0.1 GB
Updated	2026-08-07
Maintainer	mehmetkeremturkcan
Model Type	llama
Instruction-Based	Yes
Model Files	0.1 GB 0.0 GB
Model Architecture	LlamaForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.48.1
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|im_end\|>
Vocabulary Size	49152
Torch Data Type	float32
Errors	replace

Rank the SmollerLM 20M Instruct Pruned Sft5 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 SmollerLM 20M Instruct Pruned Sft5

Best Alternatives	Context / RAM	Downloads	Likes
EAGLE3 GPT Oss 20B	128K / 0.7 GB	507	0
Bagel 20B V04 Llama	32K / 39.6 GB	6	7
Bagel DPO 20B V04 Llama	32K / 39.6 GB	7	3
...lm2 1.7B Distilled GPT Oss 20B	8K / 0 GB	35	3
...runed Base PostPruneRetraining	8K / 0 GB	5	0
Rose 20B	4K / 39.9 GB	114	46
...I Llama2 Ko En Instruct 20B V1	2K / 40.4 GB	5	0
Rose 20B GPTQ	4K / 10.5 GB	4	3
Rose 20B AWQ	4K / 10.9 GB	1	1

Note: green Score (e.g. "73.2") means that the model is better than mehmetkeremturkcan/SmollerLM-20M-Instruct-Pruned-sft5.