What are the hardware requirements for Annealing Sft Fixed Tokenization 2?

Annealing Sft Fixed Tokenization 2 requires approximately 1.5 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Annealing Sft Fixed Tokenization 2 and how large is it?

Annealing Sft Fixed Tokenization 2 is developed by SaketR1, a model with 0.8b 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 Annealing Sft Fixed Tokenization 2?

Annealing Sft Fixed Tokenization 2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Annealing Sft Fixed Tokenization 2 by SaketR1 — VRAM 1.5GB, 256K context

Name: Annealing Sft Fixed Tokenization 2
Author: SaketR1

Annealing Sft Fixed Tokenization 2 is an open-source language model by SaketR1. Features: 0.8b LLM, VRAM: 1.5GB, Context: 256K, LLM Explorer Score: 0.22.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.5-0.8b Conversational Endpoints compatible Generated from trainer Qwen3 5 text Region:us Safetensors Sft Trl

Model Card on HF 🤗: https://huggingface.co/SaketR1/annealing-sft-fixed-tokenization-2

Annealing Sft Fixed Tokenization 2 Parameters and Internals

LLM Name	Annealing Sft Fixed Tokenization 2
Repository 🤗	https://huggingface.co/SaketR1/annealing-sft-fixed-tokenization-2
Model Name	annealing-sft-fixed-tokenization-2
Base Model(s)	Qwen/Qwen3.5-0.8B Qwen/Qwen3.5-0.8B
Model Size	0.8b
Required VRAM	1.5 GB
Updated	2026-03-31
Maintainer	SaketR1
Model Type	qwen3_5_text
Model Files	1.5 GB 0.0 GB
Model Architecture	Qwen3_5ForCausalLM
Context Length	262144
Model Max Length	262144
Transformers Version	5.3.0.dev0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Errors	replace

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Note: green Score (e.g. "73.2") means that the model is better than SaketR1/annealing-sft-fixed-tokenization-2.