Annealing Sft Fixed Tokenization 2 by SaketR1

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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: 0.26.

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

Annealing Sft Fixed Tokenization 2 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Annealing Sft Fixed Tokenization 2 Parameters and Internals

LLM NameAnnealing Sft Fixed Tokenization 2
Repository 🤗https://huggingface.co/SaketR1/annealing-sft-fixed-tokenization-2 
Model Nameannealing-sft-fixed-tokenization-2
Base Model(s)  Qwen/Qwen3.5-0.8B   Qwen/Qwen3.5-0.8B
Model Size0.8b
Required VRAM1.5 GB
Updated2026-03-31
MaintainerSaketR1
Model Typeqwen3_5_text
Model Files  1.5 GB   0.0 GB
Model ArchitectureQwen3_5ForCausalLM
Context Length262144
Model Max Length262144
Transformers Version5.3.0.dev0
Tokenizer ClassTokenizersBackend
Padding Token<|endoftext|>
Vocabulary Size248320
Errorsreplace

Best Alternatives to Annealing Sft Fixed Tokenization 2

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Context / RAM
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St4 Annealing Sft256K / 1.5 GB4250
...wen3.5 0.8B TW CivicAligned V1256K / 1.5 GB1130
St4 Generic Sft256K / 1.5 GB240
Qwen3.5 Text 0.8B Bnb 4bit256K / 0.8 GB4220
Note: green Score (e.g. "73.2") means that the model is better than SaketR1/annealing-sft-fixed-tokenization-2.

Rank the Annealing Sft Fixed Tokenization 2 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  

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Release v20260328a