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--- |
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tags: |
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- autotrain |
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- text-generation |
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widget: |
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- text: Once upon a time, |
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- text: My name is john and my hobby is |
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- text: My hobby was playing cricket but now i |
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- text: I asked my biology teacher that |
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- text: I love playing |
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- text: I came back to home to pet my cat but then |
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- text: I never received a letter from John Lewis after he |
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license: mit |
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language: |
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- en |
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--- |
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# NeXGen - A Text Generative Model |
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Note- this is the large version of NeXGen series we,ll realise larger versions of NeXGen soon stay-tuned. |
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Based version of NeXGen at: [CrabfishAI/NeXGen-based](https://huggingface.co/CrabfishAI/NeXGen-based) |
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Small version of NeXGen at: [CrabfishAI/NeXGen-small](https://huggingface.co/CrabfishAI/NeXGen-small) |
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Introduction-NeXGen is a state-of-the-art text generative model designed to meet diverse needs, from creative writing to content creation. This model leverages advanced natural language processing techniques to provide human-like text generation with a wide range of applications. |
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## Features |
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- **Creative Content Generation:** NeXGen excels at generating creative writing, including stories, poetry, and fictional narratives. |
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- **Contextual Awareness:** The model understands context, ensuring coherent and contextually appropriate responses. |
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- **User-Friendly Interface:** NeXGen offers an intuitive and user-friendly interface for seamless integration into various applications. |
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- **Versatility:** From content creation to educational support, NeXGen adapts to different writing styles and applications. |
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- **Advanced Architecture:** Built on the latest advancements in natural language processing, NeXGen offers high-quality text generation. |
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## Uses |
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NeXGen finds application in various domains, including: |
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- **Content Creation:** Generate marketing copy, stories, and product descriptions. |
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- **Assistance in Writing:** Aid authors, bloggers, and students in drafting articles and essays. |
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- **Chatbot Development:** Power conversational agents with human-like responses. |
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- **Prototyping and Idea Generation:** Facilitate brainstorming sessions for product development. |
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- **Social Media Content:** Generate engaging captions for social media posts. |
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- **Personal Assistant Applications:** Assist users in drafting emails and messages. |
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## Direct Use Cases |
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NeXGen can be directly employed for: |
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- **Automated Email Drafting:** Quickly compose emails with NeXGen's assistance. |
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- **Blog Post Generation:** Generate sections or entire articles based on a given topic. |
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- **Code Commenting:** Improve code documentation with clear and concise comments. |
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- **Storyline Creation for Games:** Create dynamic and engaging storylines for video games. |
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- **Learning Material Generation:** Develop study guides and educational content. |
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- **Personal Journaling Assistance:** Receive prompts and suggestions for journaling. |
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## Getting Started |
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To download NeXGen use this code: |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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# Specify the model name from Hugging Face Model Hub |
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model_name = "CrabfishAI/NeXGen-large" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained(model_name) |
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def generate_text(prompt, max_length=100, num_beams=5, no_repeat_ngram_size=2, top_k=50, top_p=0.95, temperature=0.7): |
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input_ids = tokenizer.encode(prompt, return_tensors="pt") |
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# Ensure attention_mask is provided |
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attention_mask = input_ids.ne(tokenizer.pad_token_id).float() |
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# Generate output text |
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output = model.generate( |
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input_ids, |
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max_length=max_length, |
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num_beams=num_beams, |
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no_repeat_ngram_size=no_repeat_ngram_size, |
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top_k=top_k, |
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top_p=top_p, |
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temperature=temperature, |
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attention_mask=attention_mask # Pass attention_mask to the generation method |
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) |
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decoded_output = tokenizer.decode(output[0], skip_special_tokens=True) |
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return decoded_output |
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# Example usage: |
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prompt = "Your prompt here" |
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generated_text = generate_text(prompt, max_length=200) |
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print("Generated Text:") |
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print(generated_text) |
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``` |
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## Limitation |
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1. **Content Quality**: The model's output may vary in quality, and there's a possibility it might generate content that is nonsensical, irrelevant, or grammatically incorrect. |
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2. **Bias and Sensitivity**: The model is trained on diverse data, but it may inadvertently exhibit biases or generate content that is sensitive or inappropriate. Exercise caution and review generated text before use. |
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3. **Inappropriate Language**: The model might generate text that includes offensive language or inappropriate content. Be mindful of this, especially in applications where maintaining a respectful and inclusive tone is essential. |
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4. **Ambiguous Prompts**: The quality of generated text is highly dependent on the prompt provided. Ambiguous or unclear prompts may result in less coherent or relevant outputs. |
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## Disclaimer |
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- **Use with Caution**: This model is a tool that should be used with caution. Always review and validate the generated text before incorporating it into any application or publication. |
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- **Not for Critical Applications**: Avoid using the model for critical applications where accuracy and reliability are paramount. The model is intended for creative and exploratory purposes. |
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- **Ongoing Improvement**: The model may be updated or fine-tuned for better performance. Stay informed about updates and consider using the latest version for improved results. |