FauzanAriyatmoko/qwen2.5-1.5b-alpaca-id-sft-fauzan
TEXT GENERATIONPricing:Input $0.04 / Cached $0.008 / Output $0.08Concurrent Unit Cost:1Model Size:1.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Sep 2, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
FauzanAriyatmoko/qwen2.5-1.5b-alpaca-id-sft-fauzan is a 1.5 billion parameter Qwen2.5 model, fine-tuned by FauzanAriyatmoko, with a 32768 token context length. This model was efficiently trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. It is designed for general language tasks, leveraging its Qwen2.5 architecture for robust performance.
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Model Overview
FauzanAriyatmoko/qwen2.5-1.5b-alpaca-id-sft-fauzan is a 1.5 billion parameter language model, fine-tuned by FauzanAriyatmoko. It is based on the Qwen2.5 architecture and features a substantial context length of 32768 tokens.
Key Characteristics
- Efficient Fine-tuning: This model was fine-tuned significantly faster using Unsloth and Huggingface's TRL library, indicating an optimized training process.
- Base Model: It is fine-tuned from
unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit, inheriting the capabilities of the Qwen2.5 instruction-tuned base. - License: The model is released under the Apache-2.0 license.
Potential Use Cases
- General Language Tasks: Suitable for a wide range of natural language processing applications due to its Qwen2.5 foundation.
- Resource-Efficient Deployment: The 1.5 billion parameter size makes it a good candidate for applications where computational resources are a consideration, especially given its optimized training.