--- license: apache-2.0 tags: - moe - frankenmoe - merge - mergekit - lazymergekit - Locutusque/TinyMistral-248M-v2.5-Instruct - Locutusque/TinyMistral-248M-v2.5-Instruct - Locutusque/TinyMistral-248M-v2.5-Instruct - jtatman/tinymistral-samantha-chatml-lora-v2 base_model: - Locutusque/TinyMistral-248M-v2.5-Instruct - Locutusque/TinyMistral-248M-v2.5-Instruct - Locutusque/TinyMistral-248M-v2.5-Instruct - jtatman/tinymistral-samantha-chatml-lora-v2 --- # TinyMistral-248m-v2.5-4x-Moe TinyMistral-248m-v2.5-4x-Moe is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [Locutusque/TinyMistral-248M-v2.5-Instruct](https://huggingface.co/Locutusque/TinyMistral-248M-v2.5-Instruct) * [Locutusque/TinyMistral-248M-v2.5-Instruct](https://huggingface.co/Locutusque/TinyMistral-248M-v2.5-Instruct) * [Locutusque/TinyMistral-248M-v2.5-Instruct](https://huggingface.co/Locutusque/TinyMistral-248M-v2.5-Instruct) * [jtatman/tinymistral-samantha-chatml-lora-v2](https://huggingface.co/jtatman/tinymistral-samantha-chatml-lora-v2) ## 🧩 Configuration ```yaml base_model: Locutusque/TinyMistral-248M-v2.5-Instruct experts: - source_model: Locutusque/TinyMistral-248M-v2.5-Instruct positive_prompts: - "Write me a Python program that calculates the factorial of n." - "Help me debug this code." - "Optimize this C++ program." negative_prompts: - "How do you" - "Explain the concept of" - "Give an overview of" - "Compare and contrast between" - "Provide information about" - "Help me understand" - "Summarize" - "Make a recommendation on" - "Answer this question" - "Craft me a list of some nice places to visit around the world." - "Write me a story" - "Write me an essay" - "How do I incorporate visual elements into my writing?" - source_model: Locutusque/TinyMistral-248M-v2.5-Instruct positive_prompts: - "What is the product of 2 x 5 x 18?" - "How do I guess the value of x for the function f(x) = x^4 - 2x^2 - 1?" negative_prompts: - "Help me debug this code." - "Optimize this C# script." - "Implement this feature using JavaScript." - "Convert this HTML structure into a more efficient design." - "Assist me with writing a program that" - "Craft me a list of some nice places to visit around the world. " - "Write me a story" - "Write me an essay" - "How do I incorporate visual elements into my writing?" - source_model: Locutusque/TinyMistral-248M-v2.5-Instruct positive_prompts: - "How do I incorporate fewer visual elements into my art but retain impact?" negative_prompts: - "Help me debug this code." - "Optimize this C# script." - "Implement this feature using JavaScript." - "Convert this HTML structure into a more efficient design." - "Help me debug this code." - "Optimize this C# script." - "Implement this feature using JavaScript." - "Convert this HTML structure into a more efficient design." - "Compare and contrast between" - "Provide information about" - "Help me understand" - "Summarize" - "Make a recommendation on" - "Answer this question" - "Craft me a list of some nice places to visit around the world. " - "Write me a story" - "Write me an essay" - source_model: jtatman/tinymistral-samantha-chatml-lora-v2 positive_prompts: - "Craft me a list of some nice places to visit around the world. " - "Write me a story" - "Write me an essay" - "Create a fantasy story about" - "Tell me about the wild fjords." negative_prompts: - "Help me debug this code." - "Optimize this C# script." - "Implement this feature using JavaScript." - "Convert this HTML structure into a more efficient design." - "Help me debug this code." - "Optimize this C# script." - "Implement this feature using JavaScript." - "Convert this HTML structure into a more efficient design." - "Compare and contrast between" - "Provide information about" - "Help me understand" - "Summarize" - "Make a recommendation on" - "Answer this question" - "How do I incorporate visual elements into my writing?" gate_mode: hidden ``` ## 💻 Usage ```python !pip install -qU transformers bitsandbytes accelerate from transformers import AutoTokenizer import transformers import torch model = "jtatman/TinyMistral-248m-v2.5-4x-Moe" tokenizer = AutoTokenizer.from_pretrained(model) pipeline = transformers.pipeline( "text-generation", model=model, model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True}, ) messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}] prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) print(outputs[0]["generated_text"]) ```