What are the hardware requirements for Sapling 505M Midtrain?

Sapling 505M Midtrain requires approximately 2 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 Sapling 505M Midtrain and how large is it?

Sapling 505M Midtrain is developed by VinayRevanuru, a model with 505m 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 Sapling 505M Midtrain?

Sapling 505M Midtrain is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Sapling 505M Midtrain by VinayRevanuru — VRAM 2GB, 2K context

Name: Sapling 505M Midtrain
Author: VinayRevanuru

Sapling 505M Midtrain is an open-source language model by VinayRevanuru. Features: 505m LLM, VRAM: 2GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.31.

Annealing Base model:finetune:vinayrevan... Base model:vinayrevanuru/sapli... Conversational Dataset:huggingfacefw/fineweb-... Dataset:huggingfacetb/finemath Dataset:huggingfacetb/smollm-c... Dataset:huggingfacetb/smoltalk En Endpoints compatible Math Mid-training Qwen3 Region:us Safetensors Small-language-model

Model Card on HF 🤗: https://huggingface.co/VinayRevanuru/Sapling-505M-Midtrain

Sapling 505M Midtrain Parameters and Internals

LLM Name	Sapling 505M Midtrain
Repository 🤗	https://huggingface.co/VinayRevanuru/Sapling-505M-Midtrain
Base Model(s)	Sapling 505M Base VinayRevanuru/Sapling-505M-Base
Model Size	505m
Required VRAM	2 GB
Updated	2026-10-28
Maintainer	VinayRevanuru
Model Type	qwen3
Model Files	2.0 GB
Supported Languages	en
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.51.3
Tokenizer Class	PreTrainedTokenizer
Padding Token	<\|pad\|>
Vocabulary Size	32768
Torch Data Type	float32

Rank the Sapling 505M Midtrain 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

Best Alternatives to Sapling 505M Midtrain

Best Alternatives	Context / RAM	Downloads	Likes
Sapling 505M SFT	2K / 2 GB	276	1
Sapling 505M Base	2K / 2 GB	135	0

Note: green Score (e.g. "73.2") means that the model is better than VinayRevanuru/Sapling-505M-Midtrain.