What are the hardware requirements for Sft Model?

Sft Model requires approximately 15.2 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 Sft Model and how large is it?

Sft Model is developed by AravindS373, a model with 7b 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 Sft Model?

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

Sft Model by AravindS373 — VRAM 15.2GB, 32K context

Name: Sft Model
Author: AravindS373

Sft Model is an open-source language model by AravindS373. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, Code Generating, LLM Explorer Score: 0.17.

4bit Codegen Conversational En Endpoints compatible Instruct Quantized Qwen2 Region:us Safetensors Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/AravindS373/sft_model

Sft Model Parameters and Internals

LLM Name	Sft Model
Repository 🤗	https://huggingface.co/AravindS373/sft_model
Base Model(s)	unsloth/qwen2.5-coder-7b-instruct-bnb-4bit unsloth/qwen2.5-coder-7b-instruct-bnb-4bit
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-10-21
Maintainer	AravindS373
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.3 GB: 3-of-4 1.1 GB: 4-of-4
Supported Languages	en
Quantization Type	4bit
Generates Code	Yes
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.51.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|PAD_TOKEN\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Sft Model 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 Sft Model

Best Alternatives	Context / RAM	Downloads	Likes
Kronumos Kairos V2	32K / 15.2 GB	915	2
Qwen2.5 7B Security Cot	32K / 15.2 GB	364	2
Text2sql Qwen2.5 Duckdb	32K / 15.2 GB	336	1
...query Qwen2.5 7B V5.2 Hardened	32K / 15.2 GB	118	1
Securereview 7B Mlx 4bit	32K / 4.3 GB	22	4
...2.5 Coder 7B Instruct Bnb 4bit	32K / 5.5 GB	74132	13
Qwen2.5 CoderX 7B V0.7	32K / 15.2 GB	5	2
Qwen2.5 Coder 7B Instruct 4bit	32K / 4.3 GB	13602	17
Qwen2.5 CoderX 7B V0.5	32K / 15.2 GB	6	2
UIGEN 7B 16bit	32K / 15.2 GB	14	5

Note: green Score (e.g. "73.2") means that the model is better than AravindS373/sft_model.