alibidaran/MITI_GPT_OSS_20BV1_merged
The alibidaran/MITI_GPT_OSS_20BV1_merged is a 20 billion parameter GPT-OSS model developed by alibidaran, fine-tuned from unsloth/gpt-oss-20b-unsloth-bnb-4bit. This model was trained with Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. It offers a 32768 token context length, making it suitable for applications requiring extensive context processing.
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Model Overview
alibidaran/MITI_GPT_OSS_20BV1_merged is a 20 billion parameter language model developed by alibidaran. It is a fine-tuned version of the unsloth/gpt-oss-20b-unsloth-bnb-4bit base model, leveraging the Unsloth library in conjunction with Huggingface's TRL library for training.
Key Characteristics
- Parameter Count: 20 billion parameters, offering substantial capacity for complex language tasks.
- Context Length: Supports a 32768 token context window, enabling the processing of long inputs and generating coherent, extended outputs.
- Training Efficiency: The model was trained with Unsloth, which is noted for providing a 2x speedup in the training process, indicating an optimized and efficient development approach.
- License: Distributed under the Apache-2.0 license, allowing for broad use and modification.
Potential Use Cases
This model is well-suited for applications that benefit from a large parameter count and extended context, such as:
- Advanced text generation and completion.
- Complex question answering and summarization over long documents.
- Code generation and analysis, given its GPT-OSS lineage.
- Research and development in large language models, particularly for those interested in efficient fine-tuning techniques.