lhpku20010120/llama3.1-8b-k12kgraph
lhpku20010120/llama3.1-8b-k12kgraph is an 8 billion parameter LlamaForCausalLM model, fine-tuned from meta-llama/Llama-3.1-8B using full-parameter supervised fine-tuning. It was trained on the K12-Train dataset, specifically optimized for K-12 educational question answering and knowledge-intensive reasoning. This model excels in generating responses for educational content in both Chinese and English, leveraging a 32,768 token context length.
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Model Overview
lhpku20010120/llama3.1-8b-k12kgraph is an 8 billion parameter LlamaForCausalLM, built upon the meta-llama/Llama-3.1-8B base model. It underwent full-parameter supervised fine-tuning (SFT) using the K12-Train dataset, which is associated with the K12-KGraph project. This specialized training focuses on K-12 educational question answering and knowledge-intensive reasoning.
Key Capabilities
- Specialized Domain: Optimized for K-12 educational content, providing answers and reasoning for school-level questions.
- Bilingual Support: Capable of processing and generating content in both Chinese and English.
- Extended Context: Utilizes a context length of 32,768 tokens during preprocessing, allowing for more comprehensive understanding of longer educational texts.
- Llama 3.1 Compatibility: Uses the Llama 3.1 chat format and is built with the Llama 3.1 Community License.
Intended Use Cases
This model is primarily intended for:
- Research on K-12 educational question answering.
- Knowledge-intensive reasoning within educational contexts.
- Evaluation of models trained with knowledge-graph-derived educational data.
Limitations
Users should be aware that the model may:
- Reproduce biases or errors from its base model or training data.
- Generate incorrect, incomplete, or hallucinated answers, and should not be considered an authoritative source for high-stakes decisions.
- Experience degraded performance outside its strongest domain of K-12 educational content.