What are the hardware requirements for Microllama Python Instruct 0.3 4bit?

Microllama Python Instruct 0.3 4bit requires approximately 0.4 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 Microllama Python Instruct 0.3 4bit and how large is it?

Microllama Python Instruct 0.3 4bit is developed by balrogbob, a model with 312.2m 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 Microllama Python Instruct 0.3 4bit?

Microllama Python Instruct 0.3 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Microllama Python Instruct 0.3 4bit by balrogbob — VRAM 0.4GB, 8K context

Name: Microllama Python Instruct 0.3 4bit
Author: balrogbob

Microllama Python Instruct 0.3 4bit is an open-source language model by balrogbob. Features: 312.2m LLM, VRAM: 0.4GB, Context: 8K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.13.

4-bit 4bit Base model:keeeeenw/microllama Base model:quantized:keeeeenw/... Bitsandbytes En Endpoints compatible Instruct Llama Quantized Region:us Safetensors Sft Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/balrogbob/microllama-python-instruct-0.3_4bit

Microllama Python Instruct 0.3 4bit Parameters and Internals

Model Type

text generation, transformers, unsloth, trl, sft

Additional Notes

This model was trained 2x faster with Unsloth and Huggingface's TRL library.

Supported Languages

en (unknown)

LLM Name	Microllama Python Instruct 0.3 4bit
Repository 🤗	https://huggingface.co/balrogbob/microllama-python-instruct-0.3_4bit
Base Model(s)	MicroLlama keeeeenw/MicroLlama
Model Size	312.2m
Required VRAM	0.4 GB
Updated	2026-05-23
Maintainer	balrogbob
Model Type	llama
Instruction-Based	Yes
Model Files	0.4 GB
Supported Languages	en
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.42.4
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	float32

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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