W-61/llama3-hh-harmless-qt045-b0p8-20260429-085449
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-rlhfdataset, 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)
- Learning Rate:
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.