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This is the **Inference component** of a 3-part **prod-ready** FTI feature-training-inference **RAG-framework LLMOps** course. \
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In this iteration, I've **replaced Falcon 7B Instruct** with the **currently-SoTa (Jan'24) Mistral-7B-Instruct-v0.2**, \
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fine-tuned using **Unsloth** on financial questions and answers generated with the help of GPT-4,
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and augmented with a 4bit QLoRa. \
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Prompt analysis and model registry is handled by **Comet LLM**, and finance news is streamed via **Bytewax** using an \
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**Alpaca API**, and then sent as a vector embedding to **Qdrant**'s serverless vector store. **LangChain** chains the prompt and \
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This is the **Inference component** of a 3-part **prod-ready** FTI feature-training-inference **RAG-framework LLMOps** course. \
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16 |
In this iteration, I've **replaced Falcon 7B Instruct** with the **currently-SoTa (Jan'24) Mistral-7B-Instruct-v0.2**, \
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+
fine-tuned using **Unsloth** on an expanded dataset of financial questions and answers generated with the help of GPT-4,
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quantized and augmented with a 4bit QLoRa. \
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\
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Prompt analysis and model registry is handled by **Comet LLM**, and finance news is streamed via **Bytewax** using an \
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**Alpaca API**, and then sent as a vector embedding to **Qdrant**'s serverless vector store. **LangChain** chains the prompt and \
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