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| import os | |
| import urllib.request | |
| import gradio as gr | |
| from llama_cpp import Llama | |
| def download_file(file_link, filename): | |
| # Checks if the file already exists before downloading | |
| if not os.path.isfile(filename): | |
| urllib.request.urlretrieve(file_link, filename) | |
| print("File downloaded successfully.") | |
| else: | |
| print("File already exists.") | |
| # Dowloading GGML model from HuggingFace | |
| ggml_model_path = "https://huggingface.co/bajrangCoder/BhagavadGita/resolve/main/bhagvat_gita-unsloth.Q4_K_M.gguf" | |
| filename = "bhagvat_gita-unsloth.Q4_K_M.gguf" | |
| download_file(ggml_model_path, filename) | |
| llm = Llama(model_path=filename, n_ctx=512, n_batch=126) | |
| def generate_text(prompt="how to face failurs in life"): | |
| output = llm( | |
| prompt, | |
| max_tokens=256, | |
| temperature=0.1, | |
| top_p=0.5, | |
| echo=False, | |
| stop=["#"], | |
| ) | |
| output_text = output["choices"][0]["text"].strip() | |
| # Remove Prompt Echo from Generated Text | |
| cleaned_output_text = output_text.replace(prompt, "") | |
| return cleaned_output_text | |
| description = "BhagavadGita" | |
| gradio_interface = gr.Interface( | |
| fn=generate_text, | |
| inputs="text", | |
| outputs="text", | |
| title="BhagavadGita", | |
| ) | |
| gradio_interface.launch() | |