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### System:
### USER:{prompt}
### Assistant:Temp: 1.0
min-p: 0.02-0.1posted soonposted soonbase_model: vicgalle/CarbonBeagle-11B
gate_mode: hidden
dtype: bfloat16
experts:
- source_model: vicgalle/CarbonBeagle-11B
positive_prompts: [Revamped]
- source_model: Sao10K/Fimbulvetr-10.7B-v1
positive_prompts: [Revamped]
- source_model: bn22/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED
positive_prompts: [Revamped]
- source_model: Yhyu13/LMCocktail-10.7B-v1
positive_prompts: [Revamed]Umbra-v2-MoE-4x10.7 is a Mixure of Experts (MoE) made with the following models:
* [vicgalle/CarbonBeagle-11B](https://huggingface.co/vicgalle/CarbonBeagle-11B)
* [Sao10K/Fimbulvetr-10.7B-v1](https://huggingface.co/Sao10K/Fimbulvetr-10.7B-v1)
* [bn22/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED](https://huggingface.co/bn22/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED)
* [Yhyu13/LMCocktail-10.7B-v1](https://huggingface.co/Yhyu13/LMCocktail-10.7B-v1)
1!pip install -qU transformers bitsandbytes accelerate
2from transformers import AutoTokenizer
3import transformers
4import torch
5
6model = "Steelskull/Umbra-v2-MoE-4x10.7"
7
8tokenizer = AutoTokenizer.from_pretrained(model)
9pipeline = transformers.pipeline(
10 "text-generation",
11 model=model,
12 model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
13)
14
15messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
16prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
17outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
18print(outputs[0]["generated_text"])