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README.md
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## Model Overview
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Phillnet, a marvel in the realm of language models, is a cutting-edge Dynamic Neural Network designed for advanced natural language processing tasks. Breaking away from conventional models, Phillnet exhibits dynamic adaptation and continuous evolution, showcasing its prowess in continual improvement. Crafted with a custom architecture, Phillnet seamlessly integrates an Innovative Growth Network, ushering in adaptability and innovation.
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## Key Features
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## Hyperparameters Overview
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Here's a concise overview of the key hyperparameters used for training the model:
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**Training Parameters**
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## Seamless Integration with Hugging Face 🤗
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("ayjays132/phillnet")
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## Model Overview
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![Text Generation](https://huggingface.co/ayjays132/phillnet/resolve/main/Model_Overview.png?download=true)
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Phillnet, a marvel in the realm of language models, is a cutting-edge Dynamic Neural Network designed for advanced natural language processing tasks. Breaking away from conventional models, Phillnet exhibits dynamic adaptation and continuous evolution, showcasing its prowess in continual improvement. Crafted with a custom architecture, Phillnet seamlessly integrates an Innovative Growth Network, ushering in adaptability and innovation.
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## Key Features
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## Hyperparameters Overview
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![Text Generation](https://huggingface.co/ayjays132/phillnet/resolve/main/Hyperameters.png?download=true)
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Here's a concise overview of the key hyperparameters used for training the model:
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**Training Parameters**
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## Seamless Integration with Hugging Face 🤗
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![Text Generation](https://huggingface.co/ayjays132/phillnet/resolve/main/Integration.png?download=true)
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("ayjays132/phillnet")
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