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+ ---
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+ license: apache-2.0
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+ tags:
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+ - moe
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+ - mergekit
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+ - merge
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+ - chinese
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+ - arabic
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+ - english
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+ - multilingual
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+ - german
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+ - french
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+ - jondurbin/bagel-dpo-34b-v0.2
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+ - jondurbin/nontoxic-bagel-34b-v0.2
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+ ---
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+
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+ # MetaModel_moe_yix2
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+
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+ This model is a Mixure of Experts (MoE) made with [mergekit](https://github.com/cg123/mergekit) (mixtral branch). It uses the following base models:
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+ * [jondurbin/bagel-dpo-34b-v0.2](https://huggingface.co/jondurbin/bagel-dpo-34b-v0.2)
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+ * [jondurbin/nontoxic-bagel-34b-v0.2](https://huggingface.co/jondurbin/nontoxic-bagel-34b-v0.2)
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+
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+ ## 🧩 Configuration
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+
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+ ```yamlbase_model: jondurbin/bagel-dpo-34b-v0.2
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+ dtype: bfloat16
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+ experts:
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+ - positive_prompts:
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+ - chat
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+ - assistant
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+ - tell me
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+ - explain
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+ source_model: jondurbin/bagel-dpo-34b-v0.2
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+ - positive_prompts:
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+ - chat
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+ - assistant
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+ - tell me
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+ - explain
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+ source_model: jondurbin/nontoxic-bagel-34b-v0.2
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+ gate_mode: hidden
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+ ```
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+
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+ ## 💻 Usage
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+
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+ ```python
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+ !pip install -qU transformers bitsandbytes accelerate
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+
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+ from transformers import AutoTokenizer
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+ import transformers
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+ import torch
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+
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+ model = "gagan3012/MetaModel_moe_yix2"
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+
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+ tokenizer = AutoTokenizer.from_pretrained(model)
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+ pipeline = transformers.pipeline(
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+ "text-generation",
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+ model=model,
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+ model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
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+ )
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+
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+ messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
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+ prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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+ outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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+ print(outputs[0]["generated_text"])
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+ ```