amkb222/tes-golden-chat-lora
TEXT GENERATIONPricing:Input $0.2 / Cached $0.028 / Output $0.32Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 28, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
amkb222/tes-golden-chat-lora is an 8 billion parameter Llama 3.1-based causal language model, developed by amkb222 and fine-tuned using Unsloth for accelerated training. This model is optimized for chat applications, leveraging its 32768-token context length for extended conversational understanding. Its primary strength lies in efficient, high-performance conversational AI tasks.
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Model Overview
amkb222/tes-golden-chat-lora is an 8 billion parameter language model fine-tuned from the unsloth/Meta-Llama-3.1-8B-bnb-4bit base model. Developed by amkb222, this model leverages the Unsloth library and Huggingface's TRL library for significantly faster training.
Key Characteristics
- Base Model: Meta-Llama-3.1-8B
- Parameter Count: 8 billion parameters
- Context Length: 32768 tokens
- Training Efficiency: Fine-tuned 2x faster using Unsloth for optimized performance.
Use Cases
This model is particularly well-suited for:
- Chat Applications: Designed for conversational AI, benefiting from its Llama 3.1 foundation and extended context window.
- Efficient Deployment: The Unsloth-optimized training suggests a focus on practical, resource-conscious applications.
- General Text Generation: Capable of various language understanding and generation tasks, building upon the robust Llama 3.1 architecture.