Quanta Models

Fine-tuned Large Language Models

Text Generation

What Quanta Does

Quanta represents our series of fine-tuned large language models specifically optimized for high-quality text generation. Built on state-of-the-art architectures and trained on diverse, high-quality datasets, Quanta models excel at understanding context and generating coherent, contextually appropriate text across various domains.

These models have been carefully fine-tuned to balance creativity with accuracy, making them ideal for applications ranging from content creation and summarization to conversational AI and code generation.

Key Features

•
High-Quality Output – Generates coherent, contextually relevant text with minimal hallucinations
•
Domain Adaptation – Fine-tuned for specific industries and use cases for optimal performance
•
Efficient Inference – Optimized for fast response times without compromising quality
•
Multilingual Support – Trained on diverse language data for global applications

Billions

Parameters

Fast

Inference Speed

High

Accuracy

How to Use

Download and Use the Tokenizer

"keyword">from transformers "keyword">import AutoTokenizer

# Download tokenizer "keyword">from Hugging Face repo
tokenizer = AutoTokenizer.from_pretrained("tokenaii/quanta-small")
text = "Hello, this is a test sentence."
tokens = tokenizer.tokenize(text)
input_ids = tokenizer.encode(text)

print("Tokens:", tokens)
print("Input IDs:", input_ids)
print("Decoded:", tokenizer.decode(input_ids))

Download the Model File Only

"keyword">from huggingface_hub "keyword">import hf_hub_download

# Download the model file (e.g., pytorch_model.bin) "keyword">from the repo
model_path = hf_hub_download(
    repo_id="tokenaii/quanta-small",
    filename="pytorch_model.bin"
)
print("Model downloaded to:", model_path)

Can I Run This Model?

Enter your system specifications to check if you can run this model (functionality coming soon):

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