What are the hardware requirements for SmollerLM2 100M Instruct Sft?

SmollerLM2 100M Instruct Sft requires approximately 0.3 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 SmollerLM2 100M Instruct Sft and how large is it?

SmollerLM2 100M Instruct Sft is developed by mehmetkeremturkcan, a model with 100m 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 SmollerLM2 100M Instruct Sft?

SmollerLM2 100M Instruct Sft is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SmollerLM2 100M Instruct Sft by mehmetkeremturkcan — VRAM 0.3GB, 8K context

Name: SmollerLM2 100M Instruct Sft
Author: mehmetkeremturkcan

SmollerLM2 100M Instruct Sft is an open-source language model by mehmetkeremturkcan. Features: 100m LLM, VRAM: 0.3GB, 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/SmollerLM2-100M-Instruct-sft

SmollerLM2 100M Instruct Sft Parameters and Internals

LLM Name	SmollerLM2 100M Instruct Sft
Repository 🤗	https://huggingface.co/mehmetkeremturkcan/SmollerLM2-100M-Instruct-sft
Model Name	SmollerLM2-100M-Instruct-sft
Base Model(s)	mehmetkeremturkcan/SmollerLM2-100M-Instruct mehmetkeremturkcan/SmollerLM2-100M-Instruct
Model Size	100m
Required VRAM	0.3 GB
Updated	2026-07-28
Maintainer	mehmetkeremturkcan
Model Type	llama
Instruction-Based	Yes
Model Files	0.3 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 SmollerLM2 100M Instruct 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

Best Alternatives to SmollerLM2 100M Instruct Sft

Best Alternatives	Context / RAM	Downloads	Likes
Stockmark 2 100B Instruct Beta	4K / 192.9 GB	13	12
Mossez 100M Coder Instruct	1K / 0.4 GB	113	0

Note: green Score (e.g. "73.2") means that the model is better than mehmetkeremturkcan/SmollerLM2-100M-Instruct-sft.