What are the hardware requirements for Coder0.1.3?

Coder0.1.3 requires approximately 7.2 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Coder0.1.3 and how large is it?

Coder0.1.3 is developed by bralynn, a model with 3.6b 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 Coder0.1.3?

Coder0.1.3 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Coder0.1.3 by bralynn — VRAM 7.2GB, 128K context

Name: Coder0.1.3
Author: bralynn

Coder0.1.3 is an open-source language model by bralynn. Features: 3.6b LLM, VRAM: 7.2GB, Context: 128K, License: apache-2.0, LLM Explorer Score: 0.19.

Base model:bralynn/omnim Base model:finetune:bralynn/om... Conversational En Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/bralynn/coder0.1.3

Coder0.1.3 Parameters and Internals

LLM Name	Coder0.1.3
Repository 🤗	https://huggingface.co/bralynn/coder0.1.3
Base Model(s)	Omnim bralynn/omnim
Model Size	3.6b
Required VRAM	7.2 GB
Updated	2026-05-15
Maintainer	bralynn
Model Type	llama
Model Files	5.0 GB: 1-of-2 2.2 GB: 2-of-2
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.53.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

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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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