What are the hardware requirements for Tinyllama Coder Sql En V0.1?

Tinyllama Coder Sql En V0.1 requires approximately 0.7 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 Tinyllama Coder Sql En V0.1 and how large is it?

Tinyllama Coder Sql En V0.1 is developed by yuiseki, a model with 1.1b 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 Tinyllama Coder Sql En V0.1?

Tinyllama Coder Sql En V0.1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Tinyllama Coder Sql En V0.1 by yuiseki — VRAM 0.7GB, 2K context

Name: Tinyllama Coder Sql En V0.1
Author: yuiseki

Tinyllama Coder Sql En V0.1 is an open-source language model by yuiseki. Features: 1.1b LLM, VRAM: 0.7GB, Context: 2K, License: apache-2.0, Quantized, Code Generating, LLM Explorer Score: 0.11.

Arxiv:1910.09700 Codegen Dataset:b-mc2/sql-create-conte... Endpoints compatible F16 Ggml Gguf Ja Llama Local-ai-hackathon Local-ai-hackathon-2024-03 Q4 Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/yuiseki/tinyllama-coder-sql-en-v0.1

Tinyllama Coder Sql En V0.1 Parameters and Internals

Supported Languages

ja ()

LLM Name	Tinyllama Coder Sql En V0.1
Repository 🤗	https://huggingface.co/yuiseki/tinyllama-coder-sql-en-v0.1
Model Size	1.1b
Required VRAM	0.7 GB
Updated	2026-07-25
Maintainer	yuiseki
Model Type	llama
Model Files	2.2 GB 2.2 GB 0.7 GB
Supported Languages	ja
GGML Quantization	Yes
GGUF Quantization	Yes
Quantization Type	gguf\|ggml\|q4\|q4_k
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Tinyllama Coder Sql En 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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Note: green Score (e.g. "73.2") means that the model is better than yuiseki/tinyllama-coder-sql-en-v0.1.