W-61/llama3-hh-harmless-qt045-b0p8-20260429-085449

TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kPublished:Apr 29, 2026Architecture:Transformer Cold

W-61/llama3-hh-harmless-qt045-b0p8-20260429-085449 is an 8 billion parameter Llama 3-based language model fine-tuned by W-61. This model has been specifically fine-tuned on the Anthropic/hh-rlhf dataset, indicating an optimization for harmlessness and helpfulness in conversational AI. It is designed for applications requiring robust and safety-aligned text generation, leveraging an 8192-token context length.

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Model Overview

This model, W-61/llama3-hh-harmless-qt045-b0p8-20260429-085449, is an 8 billion parameter variant of the Llama 3 architecture. It has been fine-tuned by W-61, building upon the base model W-61/llama-3-8b-base-sft-hh-harmless-4xh200.

Key Characteristics

  • Base Model: Derived from the Llama 3 8B parameter series.
  • Fine-tuning Dataset: Optimized using the Anthropic/hh-rlhf dataset, which typically focuses on aligning models for helpfulness and harmlessness.
  • Training Hyperparameters:
    • Learning Rate: 5e-07
    • Optimizer: ADAMW_TORCH
    • Epochs: 1
    • Total Batch Size: 64 (across 4 devices with gradient accumulation)

Intended Use Cases

Given its fine-tuning on the Anthropic/hh-rlhf dataset, this model is likely suitable for applications where safety, helpfulness, and adherence to ethical guidelines in AI-generated text are paramount. This includes:

  • Content Moderation: Assisting in identifying or generating safe content.
  • Customer Support: Providing helpful and non-toxic responses.
  • Conversational AI: Developing chatbots that prioritize harmless and constructive interactions.
  • Educational Tools: Generating informative and appropriate explanations.