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}
}