What are the hardware requirements for Mcqa Sft Focus Promptuning?

Mcqa Sft Focus Promptuning requires approximately 2.4 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 Mcqa Sft Focus Promptuning and how large is it?

Mcqa Sft Focus Promptuning is developed by coralieb7, a model with 0.6b 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 Mcqa Sft Focus Promptuning?

Mcqa Sft Focus Promptuning is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mcqa Sft Focus Promptuning by coralieb7 — VRAM 2.4GB, 32K context

Name: Mcqa Sft Focus Promptuning
Author: coralieb7

Mcqa Sft Focus Promptuning is an open-source language model by coralieb7. Features: 0.6b LLM, VRAM: 2.4GB, Context: 32K, LLM Explorer Score: 0.18.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-0.6b-bas... Conversational Endpoints compatible Generated from trainer Qwen3 Region:us Safetensors Sft Trl

Model Card on HF 🤗: https://huggingface.co/coralieb7/mcqa_sft_focus_promptuning

Mcqa Sft Focus Promptuning Parameters and Internals

LLM Name	Mcqa Sft Focus Promptuning
Repository 🤗	https://huggingface.co/coralieb7/mcqa_sft_focus_promptuning
Model Name	mcqa_sft_focus_promptuning
Base Model(s)	Qwen/Qwen3-0.6B-Base Qwen/Qwen3-0.6B-Base
Model Size	0.6b
Required VRAM	2.4 GB
Updated	2026-08-04
Maintainer	coralieb7
Model Type	qwen3
Model Files	2.4 GB 0.0 GB
Model Architecture	Qwen3ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.51.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float32
Errors	replace

Rank the Mcqa Sft Focus Promptuning 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 Mcqa Sft Focus Promptuning

Best Alternatives	Context / RAM	Downloads	Likes
S1 Mini	40K / 1.5 GB	1136	180
Qwen3 Reranker 0.6B	40K / 1.2 GB	2508313	377
Meridian Ac Nano	40K / 1.2 GB	456	1
Blake Haiku 1	40K / 1.2 GB	386	0
Tenorio 0.6B	40K / 1.2 GB	251	2
Qwen3 0.6B FP8	40K / 1.1 GB	1581403	62
Quipu 0.6B	40K / 1.2 GB	351	4
Qwen3 0.6B	40K / 1.5 GB	88	1
Privasis Cleaner 0.6B	40K / 1.2 GB	1171	18
Clary 0.6 0.6B	40K / 1.2 GB	158	1

Note: green Score (e.g. "73.2") means that the model is better than coralieb7/mcqa_sft_focus_promptuning.