RichardErkhov/Raj-Maharajwala_-_Open-Insurance-LLM-Llama3-8B-gguf

Quantization made by Richard Erkhov.

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Open-Insurance-LLM-Llama3-8B - GGUF

• —Model creator: https://huggingface.co/Raj-Maharajwala/
• —Original model: https://huggingface.co/Raj-Maharajwala/Open-Insurance-LLM-Llama3-8B/

Original model description: --- language:

• —en libraryname: transformers pipelinetag: text-generation tags:
• —Text Generation
• —Transformers
• —llama
• —llama-3
• —8B
• —nvidia
• —facebook
• —meta
• —LLM
• —insurance
• —research
• —pytorch
• —instruct
• —chatqa-1.5
• —chatqa
• —finetune
• —gpt4
• —conversational
• —text-generation-inference datasets:
• —InsuranceQA

base_model: "nvidia/Llama3-ChatQA-1.5-8B" finetuned: "Raj-Maharajwala/Open-Insurance-LLM-Llama3-8B" quantized: "Raj-Maharajwala/Open-Insurance-LLM-Llama3-8B-GGUF" license: llama3 ---

Open-Insurance-LLM-Llama3-8B

This model is a domain-specific language model based on Nvidia Llama 3 ChatQA, fine-tuned for insurance-related queries and conversations. It leverages the architecture of Llama 3 and is specifically trained to handle insurance domain tasks.

Model Details

• —Model Type: Instruction-tuned Language Model
• —Base Model: nvidia/Llama3-ChatQA-1.5-8B
• —Finetuned Model: Raj-Maharajwala/Open-Insurance-LLM-Llama3-8B
• —Quantized Model: Raj-Maharajwala/Open-Insurance-LLM-Llama3-8B-GGUF
• —Model Architecture: Llama
• —Parameters: 8.05 billion
• —Developer: Raj Maharajwala
• —License: llama3
• —Language: English

Quantized Model

Raj-Maharajwala/Open-Insurance-LLM-Llama3-8B-GGUF: https://huggingface.co/Raj-Maharajwala/Open-Insurance-LLM-Llama3-8B-GGUF

Training Data

The model has been fine-tuned on the InsuranceQA dataset using LoRA (8 bit), which contains insurance-specific question-answer pairs and domain knowledge. trainable params: 20.97M || all params: 8.05B || trainable %: 0.26%

LoraConfig(
  r=8,
  lora_alpha=32,
  lora_dropout=0.05,
  bias="none",
  task_type="CAUSAL_LM",
  target_modules=['up_proj', 'down_proj', 'gate_proj', 'k_proj', 'q_proj', 'v_proj', 'o_proj']
)

Model Architecture

The model uses the Llama 3 architecture with the following key components:

• —8B parameter configuration
• —Enhanced attention mechanisms from Llama 3
• —ChatQA 1.5 instruction-tuning framework
• —Insurance domain-specific adaptations

Files in Repository

• —Model Files:
• —model-00001-of-00004.safetensors (4.98 GB)
• —model-00002-of-00004.safetensors (5 GB)
• —model-00003-of-00004.safetensors (4.92 GB)
• —model-00004-of-00004.safetensors (1.17 GB)
• —model.safetensors.index.json (24 kB)

• —Tokenizer Files:
• —tokenizer.json (17.2 MB)
• —tokenizer_config.json (51.3 kB)
• —special_tokens_map.json (335 Bytes)

• —Configuration Files:
• —config.json (738 Bytes)
• —generation_config.json (143 Bytes)

Use Cases

This model is specifically designed for:

• —Insurance policy understanding and explanation
• —Claims processing assistance
• —Coverage analysis
• —Insurance terminology clarification
• —Policy comparison and recommendations
• —Risk assessment queries
• —Insurance compliance questions

Limitations

• —The model's knowledge is limited to its training data cutoff
• —Should not be used as a replacement for professional insurance advice
• —May occasionally generate plausible-sounding but incorrect information

Bias and Ethics

This model should be used with awareness that:

• —It may reflect biases present in insurance industry training data
• —Output should be verified by insurance professionals for critical decisions
• —It should not be used as the sole basis for insurance decisions
• —The model's responses should be treated as informational, not as legal or professional advice

Citation and Attribution

If you use this model in your research or applications, please cite:

@misc{maharajwala2024openinsurance,
  author = {Raj Maharajwala},
  title = {Open-Insurance-LLM-Llama3-8B},
  year = {2024},
  publisher = {HuggingFace},
  url = {https://huggingface.co/Raj-Maharajwala/Open-Insurance-LLM-Llama3-8B}
}