--- license: apache-2.0 tags: - moe - merge - mergekit - kodonho/SolarM-SakuraSolar-SLERP - Sao10K/Sensualize-Solar-10.7B - NousResearch/Nous-Hermes-2-SOLAR-10.7B - fblgit/UNA-SOLAR-10.7B-Instruct-v1.0 --- # Umbra-MoE-4x10.7 Umbra-MoE-4x10.7 is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [kodonho/SolarM-SakuraSolar-SLERP](https://huggingface.co/kodonho/SolarM-SakuraSolar-SLERP) * [Sao10K/Sensualize-Solar-10.7B](https://huggingface.co/Sao10K/Sensualize-Solar-10.7B) * [NousResearch/Nous-Hermes-2-SOLAR-10.7B](https://huggingface.co/NousResearch/Nous-Hermes-2-SOLAR-10.7B) * [fblgit/UNA-SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/fblgit/UNA-SOLAR-10.7B-Instruct-v1.0) ## 🧩 Configuration ```yamlbase_model: kodonho/SolarM-SakuraSolar-SLERP gate_mode: hidden dtype: bfloat16 experts: - source_model: kodonho/SolarM-SakuraSolar-SLERP positive_prompts: - "versatile" - "helpful" - "factual" - "integrated" - "adaptive" - "comprehensive" - "balanced" negative_prompts: - "specialized" - "narrow" - "focused" - "limited" - "specific" - source_model: Sao10K/Sensualize-Solar-10.7B positive_prompts: - "creative" - "chat" - "discuss" - "culture" - "world" - "expressive" - "detailed" - "imaginative" - "engaging" negative_prompts: - "sorry" - "cannot" - "factual" - "concise" - "straightforward" - "objective" - "dry" - source_model: NousResearch/Nous-Hermes-2-SOLAR-10.7B positive_prompts: - "analytical" - "accurate" - "logical" - "knowledgeable" - "precise" - "calculate" - "compute" - "solve" - "work" - "python" - "javascript" - "programming" - "algorithm" - "tell me" - "assistant" negative_prompts: - "creative" - "abstract" - "imaginative" - "artistic" - "emotional" - "mistake" - "inaccurate" - source_model: fblgit/UNA-SOLAR-10.7B-Instruct-v1.0 positive_prompts: - "instructive" - "clear" - "directive" - "helpful" - "informative" negative_prompts: - "exploratory" - "open-ended" - "narrative" - "speculative" - "artistic" ``` ## 💻 Usage ```python !pip install -qU transformers bitsandbytes accelerate from transformers import AutoTokenizer import transformers import torch model = "Steelskull/Umbra-MoE-4x10.7" 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"]) ```