| | --- |
| | license: mit |
| | metrics: |
| | - code_eval |
| | pipeline_tag: text-generation |
| | tags: |
| | - LLM |
| | - Text to text |
| | - Code |
| | - Chatgpt |
| | - Llama |
| | --- |
| | |
| | ## Description |
| | CodeHelp-33b is a merge model developed by Pranav for assisting developers with code-related tasks. This model is based on the Language Model (LLM) architecture. |
| |
|
| | ## Features |
| | - **Code Assistance:** Provides recommendations and suggestions for coding tasks. |
| | - **Merge Model:** Combines multiple models for enhanced performance. |
| | - **Developed by Pranav:** Created by Pranav, a skilled developer in the field. |
| |
|
| | ## Usage |
| | 1. Load the model: |
| | python |
| | from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
|
| | model = AutoModelForCausalLM.from_pretrained("enhanceaiteam/Codehelp-33b") |
| | tokenizer = AutoTokenizer.from_pretrained("enhanceaiteam/Codehelp-33b") |
| | |
| |
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| |
|
| | 2. Generate code assistance: |
| | python |
| | input_text = "Write a function to sort a list of integers." |
| | input_ids = tokenizer.encode(input_text, return_tensors="pt") |
| | output = model.generate(input_ids, max_length=100, num_return_sequences=1) |
| | generated_code = tokenizer.decode(output[0], skip_special_tokens=True) |
| | print(generated_code) |
| | |
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| |
|
| | ## Acknowledgements |
| | - This model is based on the Hugging Face Transformers library. |
| | - Special thanks to Pranav for developing and sharing this merge model for the developer community. |
| |
|
| | ## License |
| | This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. |
| |
|
| | Please customize this template with specific details about your Model CodeHelp-30b repository. If you have any further questions or need assistance, feel free to reach out. |
| |
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