joannetai520/16_bit_stage3_trymoredata1
TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Aug 16, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The joannetai520/16_bit_stage3_trymoredata1 is an 8 billion parameter Llama-based causal language model developed by joannetai520. This model was finetuned from joannetai520/16_bit_model_trymoredata1 and uniquely optimized for training speed, achieving 2x faster training using Unsloth and Huggingface's TRL library. It is designed for applications requiring efficient and rapid fine-tuning of large language models.
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Model Overview
The joannetai520/16_bit_stage3_trymoredata1 is an 8 billion parameter Llama-based language model developed by joannetai520. This model is a finetuned iteration of joannetai520/16_bit_model_trymoredata1.
Key Characteristics
- Efficient Training: A primary differentiator of this model is its optimized training process. It was trained 2x faster than conventional methods by leveraging the Unsloth library in conjunction with Huggingface's TRL library.
- Parameter Count: With 8 billion parameters, it offers a balance between performance and computational efficiency for various NLP tasks.
- Context Length: The model supports a context length of 8192 tokens, allowing it to process and generate longer sequences of text.
Use Cases
This model is particularly well-suited for developers and researchers who prioritize:
- Rapid Experimentation: Its accelerated training makes it ideal for quick iteration and experimentation with different fine-tuning strategies.
- Resource-Efficient Fine-tuning: Users with limited computational resources can benefit from the 2x faster training speed provided by the Unsloth integration.
- Applications requiring a capable 8B parameter model: Suitable for tasks such as text generation, summarization, question answering, and more, where an 8B model's performance is adequate.