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suzall/
Llama-2-7b-chat-finetune-link-box

Name: Llama-2-7b-chat-finetune-link-box
Availability: InStock

pytorch

llama

suzall/link_box_108

NousResearch/Llama-2-7b-chat-hf

finetune

mit

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Model Card for suzall/Llama-2-7b-chat-finetune-link-box

This model is a fine-tuned version of the Llama-2 7B model, specifically designed for chat applications with a focus on "link box" related contexts.

Model Details

Model Description

Developed by: suzall
Model type: Fine-tuned Language Model for Conversational AI
Language(s) (NLP): English (primary), with understanding of technical terms related to "link box"
License: [Specify License, e.g., MIT, Apache 2.0]
Finetuned from model: Llama-2 7B (Meta AI)

Model Sources

Repository: https://huggingface.co/suzall/Llama-2-7b-chat-finetune-link-box
Demo: TODO: Insert Demo Link if Available

Uses

Direct Use

This model is intended for direct use in chatbot applications, particularly those requiring in-depth understanding and discussion of "link box" related topics.

Downstream Use

Fine-tuning this model for more specialized "link box" domains (e.g., networking, telecommunications) can enhance its performance in those areas.

Out-of-Scope Use

Misuse in generating harmful or misleading content related to "link box" technologies.
Use in highly sensitive or secure environments without proper security clearances.

Bias, Risks, and Limitations

Technical Limitations

Domain Adaptation: Performance may degrade with highly specialized or niche "link box" topics.
Emotional Intelligence: Empathetic responses might not always meet human expectations.

Recommendations

Users should be aware of the model's technical limitations and biases. For critical applications, human oversight is recommended.

How to Get Started with the Model

Inference (Running the Model)

python

from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

# Load pre-trained model tokenizer (vocabulary)
tokenizer = AutoTokenizer.from_pretrained("suzall/Llama-2-7b-chat-finetune-link-box")

# Load pre-trained model (weights)
model = AutoModelForSeq2SeqLM.from_pretrained("suzall/Llama-2-7b-chat-finetune-link-box")

# Your input query
query = "What is the primary use of a link box in networking?"

# Preprocessing input
inputs = tokenizer(query, return_tensors="pt")

# Generate response
outputs = model.generate(**inputs)

# Print response
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

API Usage (for Deployment)

Consider using the Hugging Face Transformers API or deploy via frameworks like Flask or FastAPI.

Training Details

Training Data

Dataset: Fine-tuned on a curated "link box" related conversational dataset (proprietary/custom).

Training Procedure

Training Hyperparameters

Training regime: TODO: Specify Training Regime

Evaluation

Metrics

Metric	Value
Perplexity on Fine-tuning Dataset	TODO: Insert
Conversational Flow Rating (Human Evaluation)	TODO: Insert

Environmental Impact

TODO: Calculate and Insert Environmental Impact Details

Technical Specifications

Model Architecture and Objective

Architecture: Based on Llama-2 7B, fine-tuned for conversational AI with a "link box" focus.
Objective: Generate contextually relevant and informative responses.

Compute Infrastructure

TODO: Insert Compute Infrastructure Details

Citation

bibtex

@misc{suzall/Llama-2-7b-chat-finetune-link-box,
  author = {suzall},
  title = {{Llama-2-7B Chat Finetune Link Box}},
  year = {2023},
  publisher = {Hugging Face},
  journal = {https://huggingface.co/suzall/Llama-2-7b-chat-finetune-link-box}
}

Model Card Authors

TODO: List Model Card Authors

Model Card Contact

For any issues, suggestions, or general support, please open an issue on this repository or reach out to [sujal.tamrakar@outlook.com].