Model Card for neo-blockchain-assistant

This model is a LoRA-adapter fine-tuned from the base model Mistral-7B-Instruct-v0.2. It is specifically designed to assist in blockchain-related tasks and answer questions about blockchain technology.

Model Details

Model Description

The neo-blockchain-assistant model is a lightweight fine-tuned version of the Mistral-7B-Instruct-v0.2 model using LoRA (Low-Rank Adaptation) and PEFT (Parameter-Efficient Fine-Tuning) techniques. It is optimized for text generation tasks related to blockchain technology, providing educational content and explanations.

• Developed by: TooKeen
• Funded by [optional]: N/A
• Shared by [optional]: N/A
• Model type: LoRA fine-tuned text-generation model
• Language(s) (NLP): English
• License: Apache-2.0
• Finetuned from model [optional]: Mistral-7B-Instruct-v0.2

Model Sources [optional]

• Repository: https://huggingface.co./TooKeen/neo-blockchain-assistant
• Paper [optional]: N/A
• Demo [optional]: N/A

Uses

Direct Use

This model can be used directly for generating blockchain-related text content, answering questions, and providing explanations about blockchain technology. It can be used for educational purposes, content creation, or blockchain research assistance.

Downstream Use [optional]

The model can be further fine-tuned for specific blockchain-related use cases or integrated into larger systems where blockchain education or customer service is required.

Out-of-Scope Use

This model should not be used for non-blockchain-related tasks or sensitive domains where accuracy in unrelated fields is crucial.

Bias, Risks, and Limitations

As this model is fine-tuned specifically for blockchain-related content, it may not generalize well to other domains. The model could provide biased or incomplete information on blockchain-related topics, depending on the training data. Use it with caution for legal, financial, or high-stakes decisions.

Recommendations

Users should be aware that the model's outputs are based on blockchain-related training data and may not reflect up-to-date or completely accurate information on complex or evolving topics. It is recommended to cross-check any critical information generated by the model.

How to Get Started with the Model

Use the code below to get started with the model:

from huggingface_hub import InferenceClient

client = InferenceClient(
    model="TooKeen/neo-blockchain-assistant",  # Your model name
    token="your_token_here"  # Your Hugging Face API token
)

result = client.text_generation("What is blockchain?")
print(result)