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  library_name: transformers
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- tags: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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- # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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  ## Model Details
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- ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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- ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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- ### Downstream Use [optional]
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- [More Information Needed]
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- ## Training Details
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- ### Training Data
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- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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- [More Information Needed]
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- [More Information Needed]
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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Dataset Card if possible. -->
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- <!-- Relevant interpretability work for the model goes here -->
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- [More Information Needed]
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- ## Environmental Impact
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- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- ### Compute Infrastructure
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- #### Hardware
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- #### Software
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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- [More Information Needed]
 
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  ---
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+ language:
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+ - en
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  library_name: transformers
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+ pipeline_tag: text-generation
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+ tags:
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+ - Text Generation
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+ - Transformers
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+ - llama
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+ - llama-3
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+ - 8B
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+ - nvidia
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+ - facebook
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+ - meta
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+ - LLM
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+ - insurance
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+ - research
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+ - pytorch
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+ - instruct
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+ - chatqa-1.5
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+ - chatqa
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+ - finetune
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+ - gpt4
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+ - conversational
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+ - text-generation-inference
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+ datasets:
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+ - InsuranceQA
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+ base_model: "nvidia/Llama3-ChatQA-1.5-8B"
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+ license: llama3
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  ---
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+ # Open-Insurance-LLM-Llama3-8B
 
 
 
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+ This model is a domain-specific language model based on Llama 3, fine-tuned for insurance-related queries and conversations. It leverages the architecture of Llama 3 and is specifically trained to handle insurance domain tasks.
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  ## Model Details
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+ - **Model Type:** Instruction-tuned Language Model
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+ - **Base Model:** nvidia/Llama3-ChatQA-1.5-8B
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+ - **Finetuned Model:** Raj-Maharajwala/Open-Insurance-LLM-Llama3-8B
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+ - **Model Architecture:** Llama
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+ - **Parameters:** 8.05 billion
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+ - **Developer:** Raj Maharajwala
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+ - **License:** llama3
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+ - **Language:** English
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+
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+ ### Quantized Model:
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+ Raj-Maharajwala/Open-Insurance-LLM-Llama3-8B-GGUF
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+ (https://huggingface.co/Raj-Maharajwala/Open-Insurance-LLM-Llama3-8B-GGUF)
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+
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+ ## Training Data
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+ The model has been fine-tuned on the InsuranceQA dataset, which contains insurance-specific question-answer pairs and domain knowledge.
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+ trainable params: 20.97M || all params: 8.05B || trainable%: 0.26%
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+ ## Model Architecture
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+ The model uses the Llama 3 architecture with the following key components:
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+ - 8B parameter configuration
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+ - Enhanced attention mechanisms from Llama 3
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+ - ChatQA 1.5 instruction-tuning framework
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+ - Insurance domain-specific adaptations
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+
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+ ## Files in Repository
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+ - **Model Files:**
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+ - `model-00001-of-00004.safetensors` (4.98 GB)
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+ - `model-00002-of-00004.safetensors` (5 GB)
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+ - `model-00003-of-00004.safetensors` (4.92 GB)
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+ - `model-00004-of-00004.safetensors` (1.17 GB)
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+ - `model.safetensors.index.json` (24 kB)
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+ - **Tokenizer Files:**
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+ - `tokenizer.json` (17.2 MB)
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+ - `tokenizer_config.json` (51.3 kB)
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+ - `special_tokens_map.json` (335 Bytes)
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+ - **Configuration Files:**
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+ - `config.json` (738 Bytes)
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+ - `generation_config.json` (143 Bytes)
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+ ## Use Cases
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+ This model is specifically designed for:
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+ - Insurance policy understanding and explanation
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+ - Claims processing assistance
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+ - Coverage analysis
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+ - Insurance terminology clarification
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+ - Policy comparison and recommendations
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+ - Risk assessment queries
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+ - Insurance compliance questions
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+ ## Limitations
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+ - The model's knowledge is limited to its training data cutoff
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+ - Should not be used as a replacement for professional insurance advice
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+ - May occasionally generate plausible-sounding but incorrect information
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+ ## Bias and Ethics
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+ This model should be used with awareness that:
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+ - It may reflect biases present in insurance industry training data
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+ - Output should be verified by insurance professionals for critical decisions
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+ - It should not be used as the sole basis for insurance decisions
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+ - The model's responses should be treated as informational, not as legal or professional advice
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+ ## Citation and Attribution
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+ If you use this model in your research or applications, please cite:
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+ ```
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+ @misc{maharajwala2024openinsurance,
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+ author = {Raj Maharajwala},
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+ title = {Open-Insurance-LLM-Llama3-8B},
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+ year = {2024},
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+ publisher = {HuggingFace},
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+ url = {https://huggingface.co/Raj-Maharajwala/Open-Insurance-LLM-Llama3-8B}
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+ }
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+ ```