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Browse files- README.md +55 -0
- config.json +30 -0
- mergekit_moe_config.yml +7 -0
- model-00001-of-00013.safetensors +3 -0
- model-00002-of-00013.safetensors +3 -0
- model-00003-of-00013.safetensors +3 -0
- model-00004-of-00013.safetensors +3 -0
- model-00005-of-00013.safetensors +3 -0
- model-00006-of-00013.safetensors +3 -0
- model-00007-of-00013.safetensors +3 -0
- model-00008-of-00013.safetensors +3 -0
- model-00009-of-00013.safetensors +3 -0
- model-00010-of-00013.safetensors +3 -0
- model-00011-of-00013.safetensors +3 -0
- model-00012-of-00013.safetensors +3 -0
- model-00013-of-00013.safetensors +3 -0
- model.safetensors.index.json +1 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +43 -0
README.md
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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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- frankenmoe
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- merge
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- mergekit
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- lazymergekit
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- allknowingroger/StarlingMaxLimmy2-7B-slerp
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- Kukedlc/NeuralMaths-Experiment-7b
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base_model:
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- allknowingroger/StarlingMaxLimmy2-7B-slerp
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- Kukedlc/NeuralMaths-Experiment-7b
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---
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# StarlingMaths-12B-MoE
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StarlingMaths-12B-MoE is a Mixture of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [allknowingroger/StarlingMaxLimmy2-7B-slerp](https://huggingface.co/allknowingroger/StarlingMaxLimmy2-7B-slerp)
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* [Kukedlc/NeuralMaths-Experiment-7b](https://huggingface.co/Kukedlc/NeuralMaths-Experiment-7b)
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## 🧩 Configuration
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```yaml
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base_model: allknowingroger/StarlingMaxLimmy2-7B-slerp
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experts:
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- source_model: allknowingroger/StarlingMaxLimmy2-7B-slerp
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positive_prompts: ["why"]
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- source_model: Kukedlc/NeuralMaths-Experiment-7b
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positive_prompts: ["math"]
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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 = "allknowingroger/StarlingMaths-12B-MoE"
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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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```
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config.json
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{
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"_name_or_path": "allknowingroger/StarlingMaxLimmy2-7B-slerp",
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"architectures": [
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"MixtralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mixtral",
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"num_attention_heads": 32,
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"num_experts_per_tok": 2,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"num_local_experts": 2,
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"output_router_logits": false,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"router_aux_loss_coef": 0.001,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.39.3",
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"use_cache": true,
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"vocab_size": 32000
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}
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mergekit_moe_config.yml
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base_model: allknowingroger/StarlingMaxLimmy2-7B-slerp
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experts:
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- source_model: allknowingroger/StarlingMaxLimmy2-7B-slerp
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positive_prompts: ["why"]
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- source_model: Kukedlc/NeuralMaths-Experiment-7b
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positive_prompts: ["math"]
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special_tokens_map.json
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tokenizer.json
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tokenizer.model
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tokenizer_config.json
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