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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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# MetaModel_moe_yix2 |
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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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## 🧩 Configuration |
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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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## 💻 Usage |
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```python |
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!pip install -qU transformers bitsandbytes accelerate |
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from transformers import AutoTokenizer |
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import transformers |
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import torch |
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model = "gagan3012/MetaModel_moe_yix2" |
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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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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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``` |
