Create README.md

README.md

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+---
+tags:
+- autotrain
+- text-generation
+widget:
+- text: "Once upon a time,"
+- text: "My name is john and my hobby is"
+- text: "My hobby was playing cricket but now i"
+- text: "I asked my biology teacher that"
+- text: "I love playing"
+- text: "I came back to home to pet my cat but then"
+- text: "I never received a letter from John Lewis after he"
+---
+
+
+
+
+# NeXGen - A Text Generative Model
+Note- this is the based version of NeXGen series we,ll realise medium, large, xl versions of NeXGen soon stay-tuned.
+
+
+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.
+
+## Features
+
+- **Creative Content Generation:** NeXGen excels at generating creative writing, including stories, poetry, and fictional narratives.
+- **Contextual Awareness:** The model understands context, ensuring coherent and contextually appropriate responses.
+- **User-Friendly Interface:** NeXGen offers an intuitive and user-friendly interface for seamless integration into various applications.
+- **Versatility:** From content creation to educational support, NeXGen adapts to different writing styles and applications.
+- **Advanced Architecture:** Built on the latest advancements in natural language processing, NeXGen offers high-quality text generation.
+
+## Uses
+
+NeXGen finds application in various domains, including:
+
+- **Content Creation:** Generate marketing copy, stories, and product descriptions.
+- **Assistance in Writing:** Aid authors, bloggers, and students in drafting articles and essays.
+- **Chatbot Development:** Power conversational agents with human-like responses.
+- **Prototyping and Idea Generation:** Facilitate brainstorming sessions for product development.
+- **Social Media Content:** Generate engaging captions for social media posts.
+- **Personal Assistant Applications:** Assist users in drafting emails and messages.
+
+## Direct Use Cases
+
+NeXGen can be directly employed for:
+
+- **Automated Email Drafting:** Quickly compose emails with NeXGen's assistance.
+- **Blog Post Generation:** Generate sections or entire articles based on a given topic.
+- **Code Commenting:** Improve code documentation with clear and concise comments.
+- **Storyline Creation for Games:** Create dynamic and engaging storylines for video games.
+- **Learning Material Generation:** Develop study guides and educational content.
+- **Personal Journaling Assistance:** Receive prompts and suggestions for journaling.
+
+## Getting Started
+
+To download NeXGen use this code:
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Specify the model name from Hugging Face Model Hub
+model_name = "CrabfishAI/NeXGen-based"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+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):
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+
+    # Ensure attention_mask is provided
+    attention_mask = input_ids.ne(tokenizer.pad_token_id).float()
+
+    # Generate output text
+    output = model.generate(
+        input_ids,
+        max_length=max_length,
+        num_beams=num_beams,
+        no_repeat_ngram_size=no_repeat_ngram_size,
+        top_k=top_k,
+        top_p=top_p,
+        temperature=temperature,
+        attention_mask=attention_mask  # Pass attention_mask to the generation method
+    )
+
+    decoded_output = tokenizer.decode(output[0], skip_special_tokens=True)
+    return decoded_output
+
+# Example usage:
+prompt = "Your prompt here"
+generated_text = generate_text(prompt, max_length=200)
+
+print("Generated Text:")
+print(generated_text)
+```
+
+## Limitation
+
+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.
+
+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.
+
+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.
+
+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.
+
+## Disclaimer
+
+- **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.
+
+- **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.
+
+- **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.