--- license: apache-2.0 tags: - moe - frankenmoe - merge - mergekit - lazymergekit - Open-Orca/Mistral-7B-OpenOrca - NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story - S-miguel/The-Trinity-Coder-7B - chihoonlee10/T3Q-Mistral-Orca-Math-DPO base_model: - Open-Orca/Mistral-7B-OpenOrca - NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story - S-miguel/The-Trinity-Coder-7B - chihoonlee10/T3Q-Mistral-Orca-Math-DPO --- # sixtyoneeighty-4x7b-v2 sixtyoneeighty-4x7b-v2 is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [Open-Orca/Mistral-7B-OpenOrca](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca) * [NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story](https://huggingface.co/NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story) * [S-miguel/The-Trinity-Coder-7B](https://huggingface.co/S-miguel/The-Trinity-Coder-7B) * [chihoonlee10/T3Q-Mistral-Orca-Math-DPO](https://huggingface.co/chihoonlee10/T3Q-Mistral-Orca-Math-DPO) ## 🧩 Configuration ```yaml base_model: cognitivecomputations/dolphin-2.8-mistral-7b-v02 gate_mode: hidden dtype: bfloat16 experts_per_token: 2 experts: - source_model: Open-Orca/Mistral-7B-OpenOrca positive_prompts: - "What are some fun activities to do in Seattle?" - "What are some fun historical facts about New York City?" negative_prompts: - "Write a Python script to scrape data from a website." - "Explain the key differences between Bayesian and frequentist statistics." - source_model: NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story positive_prompts: - "Write me a fictional story about dragons and wizards?" - "From now on take on the role of Dwayne Johnson" negative_prompts: - "When is the next solar eclipse." - "What year did World War II end?" - source_model: S-miguel/The-Trinity-Coder-7B positive_prompts: - "Can you review my JavaScript code and suggest ways to optimize it for better performance?" - "I'm getting an 'undefined variable' error in my Python script. Here's the code: [code snippet]" negative_prompts: - "What are some effective strategies for managing stress and anxiety?" - "Compare and contrast the themes in 'The Great Gatsby' and 'The Catcher in the Rye'." - source_model: chihoonlee10/T3Q-Mistral-Orca-Math-DPO positive_prompts: - "What's a square root of 1337?" - "Find the midpoint of the line segment with the given end points (-5,7) and (-2,1)" negative_prompts: - "What are some effective strategies for managing stress and anxiety?" - "Compare and contrast the themes in 'The Great Gatsby' and 'The Catcher in the Rye'." ``` ## 💻 Usage ```python !pip install -qU transformers bitsandbytes accelerate from transformers import AutoTokenizer import transformers import torch model = "jambroz/sixtyoneeighty-7b-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"]) ```