jumang4423/Llama-2-7b-chat-hf-jumango
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kArchitecture:Transformer Cold
The jumang4423/Llama-2-7b-chat-hf-jumango model is a 7 billion parameter language model based on the Llama 2 architecture, fine-tuned for chat applications. This model was trained using AutoTrain, indicating a focus on ease of deployment and potentially specialized conversational capabilities. With a context length of 4096 tokens, it is designed for interactive dialogue and general-purpose text generation in chat-like scenarios.
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Model Overview
The jumang4423/Llama-2-7b-chat-hf-jumango is a 7 billion parameter language model built upon the Llama 2 architecture. This model has been specifically fine-tuned for chat and conversational applications, leveraging the robust base of Llama 2.
Key Characteristics
- Architecture: Llama 2 base model.
- Parameter Count: 7 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a context window of 4096 tokens, suitable for maintaining coherent conversations over several turns.
- Training Method: The model was trained using AutoTrain, suggesting an optimized and potentially automated fine-tuning process for its specific chat-oriented task.
Use Cases
This model is well-suited for:
- Developing conversational AI agents and chatbots.
- Generating human-like responses in interactive applications.
- Text summarization and question-answering within a dialogue context.
- Prototyping and deploying chat-based language model functionalities with a readily available, fine-tuned model.