--- license: apache-2.0 tags: - moe - frankenmoe - merge - mergekit - lazymergekit - Himitsui/Kaiju-11B - Sao10K/Fimbulvetr-11B-v2 - decapoda-research/Antares-11b-v2 - beberik/Nyxene-v3-11B base_model: - Himitsui/Kaiju-11B - Sao10K/Fimbulvetr-11B-v2 - decapoda-research/Antares-11b-v2 - beberik/Nyxene-v3-11B --- # Umbra-v3-MoE-4x11b Umbra-v3-MoE-4x11b is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [Himitsui/Kaiju-11B](https://huggingface.co/Himitsui/Kaiju-11B) * [Sao10K/Fimbulvetr-11B-v2](https://huggingface.co/Sao10K/Fimbulvetr-11B-v2) * [decapoda-research/Antares-11b-v2](https://huggingface.co/decapoda-research/Antares-11b-v2) * [beberik/Nyxene-v3-11B](https://huggingface.co/beberik/Nyxene-v3-11B) ## 🧩 Configuration ```yaml base_model: vicgalle/CarbonBeagle-11B-truthy gate_mode: hidden dtype: bfloat16 experts_per_token: 4 experts: - source_model: Himitsui/Kaiju-11B positive_prompts: - "Imagine" - "Create" - "Envision" - "Fantasize" - "Invent" - "Narrate" - "Plot" - "Portray" - "Storytell" - "Visualize" - "Describe" - "Develop" - "Forge" - "Craft" - "Conceptualize" - "Dream" - "Concoct" - "Characterize" negative_prompts: - "Recite" - "Report" - "Summarize" - "Enumerate" - "List" - "Cite" - source_model: Sao10K/Fimbulvetr-11B-v2 positive_prompts: - "Dramatize" - "Embody" - "Illustrate" - "Perform" - "Roleplay" - "Simulate" - "Stage" - "Unfold" - "Weave" - "Design" - "Outline" - "Script" - "Sketch" - "Spin" - "Depict" - "Render" - "Fashion" - "Conceive" negative_prompts: - "Analyze" - "Critique" - "Dissect" - "Explain" - "Clarify" - "Interpret" - source_model: decapoda-research/Antares-11b-v2 positive_prompts: - "Solve" - "Respond" - "Convey" - "Disclose" - "Expound" - "Narrate" - "Present" - "Reveal" - "Specify" - "Uncover" - "Decode" - "Examine" - "Report" - "Survey" - "Validate" - "Verify" - "Question" - "Query" negative_prompts: - "Divert" - "Obscure" - "Overstate" - "Undermine" - "Misinterpret" - "Skew" - source_model: beberik/Nyxene-v3-11B positive_prompts: - "Explain" - "Instruct" - "Clarify" - "Educate" - "Guide" - "Inform" - "Teach" - "Detail" - "Elaborate" - "Enlighten" - "Advise" - "Interpret" - "Analyze" - "Define" - "Demonstrate" - "Illustrate" - "Simplify" - "Summarize" negative_prompts: - "Speculate" - "Fabricate" - "Exaggerate" - "Mislead" - "Confuse" - "Distort" ``` ## 💻 Usage ```python !pip install -qU transformers bitsandbytes accelerate from transformers import AutoTokenizer import transformers import torch model = "Steelskull/Umbra-v3-MoE-4x11b" 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"]) ```