--- library_name: transformers tags: - trl - sft license: apache-2.0 datasets: - gokaygokay/prompt-enhancement-75k language: - en base_model: - HuggingFaceTB/SmolLM2-135M-Instruct pipeline_tag: text-generation --- [![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory) # QuantFactory/SmolLM2-Prompt-Enhance-GGUF This is quantized version of [gokaygokay/SmolLM2-Prompt-Enhance](https://huggingface.co/gokaygokay/SmolLM2-Prompt-Enhance) created using llama.cpp # Original Model Card ```python from transformers import AutoTokenizer, AutoModelForCausalLM import torch device = "cuda" if torch.cuda.is_available() else "cpu" model_id = "gokaygokay/SmolLM2-Prompt-Enhance" tokenizer_id = "HuggingFaceTB/SmolLM2-135M-Instruct" # Load model and tokenizer tokenizer = AutoTokenizer.from_pretrained(tokenizer_id ) model = AutoModelForCausalLM.from_pretrained(model_id).to(device) # Model response generation functions def generate_response(model, tokenizer, instruction, device="cpu"): """Generate a response from the model based on an instruction.""" messages = [{"role": "user", "content": instruction}] input_text = tokenizer.apply_chat_template( messages, tokenize=False, add_generation_prompt=True ) inputs = tokenizer.encode(input_text, return_tensors="pt").to(device) outputs = model.generate( inputs, max_new_tokens=256, repetition_penalty=1.2 ) response = tokenizer.decode(outputs[0], skip_special_tokens=True) return response def print_response(response): """Print the model's response.""" print(f"Model response:") print(response.split("assistant\n")[-1]) print("-" * 100) prompt = "cat" response = generate_response(model, tokenizer, prompt, device) print_response(response) # a gray cat with white fur and black eyes is in the center of an open window on a concrete floor. # The front wall has two large windows that have light grey frames behind them. # here is a small wooden door to the left side of the frame at the bottom right corner. # A metal fence runs along both sides of the image from top down towards the middle ground. # Behind the cats face away toward the camera's view it appears as if there is another cat sitting next to the one # they're facing forward against the glass surface above their head. ``` ### Training Script https://colab.research.google.com/drive/1Gqmp3VIcr860jBnyGYEbHtCHcC49u0mo?usp=sharing