What are the hardware requirements for GOAT Coder Llama3.1 8B?

GOAT Coder Llama3.1 8B requires approximately 16.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed GOAT Coder Llama3.1 8B and how large is it?

GOAT Coder Llama3.1 8B is developed by kshabana, a model with 8b 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 GOAT Coder Llama3.1 8B?

GOAT Coder Llama3.1 8B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GOAT Coder Llama3.1 8B by kshabana — VRAM 16.1GB

Name: GOAT Coder Llama3.1 8B
Author: kshabana

GOAT Coder Llama3.1 8B is an open-source language model by kshabana. Features: 8b LLM, VRAM: 16.1GB, License: apache-2.0, Quantized, Fine-Tuned, Instruction-Based, Code Generating, LLM Explorer Score: 0.14.

4bit Base model:quantized:unsloth/m... Base model:unsloth/meta-llama-... Codegen Coding Conversational Dataset:replete-ai/code bagel En Endpoints compatible Finetuned Gguf Instruct Llama Lora Pytorch Q4 Quantized Region:us Safetensors Safetersors Sft Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/kshabana/GOAT-coder-llama3.1-8b

GOAT Coder Llama3.1 8B Parameters and Internals

Model Type

safetensors, gguf

Use Cases

Applications:

coding

Limitations:

can sometimes produce wrong answers

Additional Notes

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

Supported Languages

en (English)

Training Details

Data Sources:

https://huggingface.co/datasets/Replete-AI/code_bagel

Methodology:

Trained with Unsloth and Huggingface's TRL library

Context Length:

131072

LLM Name	GOAT Coder Llama3.1 8B
Repository 🤗	https://huggingface.co/kshabana/GOAT-coder-llama3.1-8b
Base Model(s)	unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-08-03
Maintainer	kshabana
Instruction-Based	Yes
Model Files	16.1 GB 4.9 GB 5.7 GB 8.5 GB 0.2 GB 5.0 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 1.2 GB: 4-of-4
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	q4\|4bit\|gguf\|q4_k\|q5_k
Generates Code	Yes
Model Architecture	AutoModel
License	apache-2.0
Model Max Length	131072
Is Biased	none
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|finetune_right_pad_id\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	o_proj\|k_proj\|q_proj\|down_proj\|gate_proj\|up_proj\|v_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	16

Rank the GOAT Coder Llama3.1 8B 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