4fhct4sd/ocular-QWEN3.5-4b-TR-FFT001

VISIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 26, 2026Architecture:Transformer Featherless Exclusive Cold

The 4fhct4sd/ocular-QWEN3.5-4b-TR-FFT001 model is a 4.5 billion parameter language model fine-tuned from unsloth/Qwen3.5-4B-Base. Developed by 4fhct4sd, it was trained using Supervised Fine-Tuning (SFT) with the TRL framework. This model is designed for general text generation tasks, leveraging its 32768 token context length for processing longer inputs. Its fine-tuning process aims to enhance its conversational and generative capabilities.

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Model Overview

This model, ocular-QWEN3.5-4b-TR-FFT001, is a 4.5 billion parameter language model. It is a fine-tuned variant of the unsloth/Qwen3.5-4B-Base architecture, developed by 4fhct4sd.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen3.5-4B-Base.
  • Training Method: Utilizes Supervised Fine-Tuning (SFT) for its training procedure.
  • Framework: Trained using the TRL (Transformer Reinforcement Learning) library, indicating a focus on improving model responses through fine-tuning techniques.
  • Context Length: Supports a substantial context window of 32768 tokens, allowing for the processing and generation of longer text sequences.

Potential Use Cases

  • Text Generation: Suitable for various text generation tasks, including answering open-ended questions or continuing conversations.
  • Conversational AI: Its fine-tuned nature suggests potential for engaging in more coherent and contextually relevant dialogues.
  • Exploratory Development: Can be used by developers looking to experiment with a fine-tuned Qwen3.5-4B model for specific applications.

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