What are the hardware requirements for Toam 100M V0.1?

Toam 100M V0.1 requires approximately 0.1 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Toam 100M V0.1 and how large is it?

Toam 100M V0.1 is developed by ksg91, 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 Toam 100M V0.1?

Toam 100M V0.1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Toam 100M V0.1 by ksg91 — VRAM 0.1GB, 2K context

Name: Toam 100M V0.1
Author: ksg91

Toam 100M V0.1 is an open-source language model by ksg91. Features: 100m LLM, VRAM: 0.1GB, Context: 2K, License: apache-2.0, Quantized, LLM Explorer Score: 0.33.

Agents Dataset:amazonscience/massive Dataset:argilla/apigen-functio... Dataset:bigcode/starcoderdata Dataset:code-search-net/code s... Dataset:codeparrot/codeparrot-... Dataset:huggingfacefw/fineweb-... Dataset:huggingfacetb/smollm-c... Dataset:nvidia/when2call Dataset:team-ace/toolace Dataset:wikimedia/wikipedia En Endpoints compatible Function-calling Gguf Llama Llama.cpp Q8 Quantized Region:us Safetensors Small-language-model Tool-calling Tool-use

Model Card on HF 🤗: https://huggingface.co/ksg91/toam-100m-v0.1

Toam 100M V0.1 Parameters and Internals

LLM Name	Toam 100M V0.1
Repository 🤗	https://huggingface.co/ksg91/toam-100m-v0.1
Model Size	100m
Required VRAM	0.1 GB
Updated	2026-09-30
Maintainer	ksg91
Model Type	llama
Model Files	0.2 GB 0.2 GB 0.1 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf\|q8
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	5.17.0
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|pad\|>
Vocabulary Size	32768

Rank the Toam 100M V0.1 capabilities

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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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