What are the hardware requirements for Autotrain Qwen Finetune Reason?

Autotrain Qwen Finetune Reason requires approximately 3.1 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Autotrain Qwen Finetune Reason and how large is it?

Autotrain Qwen Finetune Reason is developed by toastloaf, a model with 1.5b 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 Autotrain Qwen Finetune Reason?

Autotrain Qwen Finetune Reason is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Autotrain Qwen Finetune Reason by toastloaf — VRAM 3.1GB, 32K context

Name: Autotrain Qwen Finetune Reason
Author: toastloaf

Autotrain Qwen Finetune Reason is an open-source language model by toastloaf. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, License: other, Fine-Tuned, Instruction-Based, LLM Explorer Score: 0.17.

Autotrain Autotrain compatible Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-1.5b-i... Conversational Dataset:mlabonne/openthoughts-... Endpoints compatible Finetuned Instruct Peft Qwen2 Region:us Safetensors Tensorboard

Model Card on HF 🤗: https://huggingface.co/toastloaf/autotrain-qwen-finetune-reason

Autotrain Qwen Finetune Reason Parameters and Internals

LLM Name	Autotrain Qwen Finetune Reason
Repository 🤗	https://huggingface.co/toastloaf/autotrain-qwen-finetune-reason
Base Model(s)	Qwen/Qwen2.5-1.5B-Instruct Qwen/Qwen2.5-1.5B-Instruct
Model Size	1.5b
Required VRAM	3.1 GB
Updated	2025-04-11
Maintainer	toastloaf
Model Type	qwen2
Instruction-Based	Yes
Model Files	3.1 GB 0.0 GB
Model Architecture	Qwen2ForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.48.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151665
Torch Data Type	float16
Errors	replace

Rank the Autotrain Qwen Finetune Reason 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

Best Alternatives to Autotrain Qwen Finetune Reason

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 1.5B 1.3M Stretched	1280K / 3.1 GB	11	0
Merge Cord V1	128K / 3.1 GB	155	1
Gte Qwen2 1.5B Instruct	128K / 7.1 GB	923076	237
AceInstruct 1.5B	128K / 3.5 GB	139	22
... Abliterated TIES Qwen2.5 1.5B	128K / 3.5 GB	15	0
Saba1 1.8B	128K / 3.6 GB	6	1
Miniclaus Qw1.5B UNAMGS	128K / 3.5 GB	12	8
Bellatrix 1.5B XElite	128K / 3.5 GB	19	3
GCIRS Reasoning 1.5B R1	128K / 3.5 GB	9	1
...illed Scout 1.5B Instruct Gen1	128K / 3.5 GB	10	0

Note: green Score (e.g. "73.2") means that the model is better than toastloaf/autotrain-qwen-finetune-reason.