LunaticPython161
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Browse files- README.md +74 -0
- added_tokens.json +3 -0
- config.json +30 -0
- mergekit_moe_config.yml +26 -0
- model-00001-of-00003.safetensors +3 -0
- model-00002-of-00003.safetensors +3 -0
- model-00003-of-00003.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 +0 -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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- cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
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- LunaticPython161/CyberWitch-7B
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base_model:
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- cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
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- LunaticPython161/CyberWitch-7B
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---
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# Lily-MoE-2x7b
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Lily-MoE-2x7b is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser](https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser)
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* [LunaticPython161/CyberWitch-7B](https://huggingface.co/LunaticPython161/CyberWitch-7B)
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## 🧩 Configuration
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```yaml
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base_model: cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
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gate_mode: hidden # one of "hidden", "cheap_embed", or "random"
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dtype: bfloat16 # output dtype (float32, float16, or bfloat16)
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experts:
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- source_model: cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
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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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- "code"
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- "programming"
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- source_model: LunaticPython161/CyberWitch-7B
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positive_prompts:
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- "solve"
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- "count"
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- "math"
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- "mathematics"
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- "algorithm"
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- "cypher"
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- "cybersecurity"
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- "penetration testing"
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- "red team"
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- "blue team"
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- "hacking"
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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 = "LunaticPython161/Lily-MoE-2x7b"
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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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added_tokens.json
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{
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"<|im_start|>": 32000
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}
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config.json
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{
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"_name_or_path": "cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser",
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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": "4.37.2",
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"use_cache": false,
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"vocab_size": 32001
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}
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mergekit_moe_config.yml
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base_model: cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
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gate_mode: hidden # one of "hidden", "cheap_embed", or "random"
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dtype: bfloat16 # output dtype (float32, float16, or bfloat16)
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experts:
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- source_model: cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
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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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- "code"
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- "programming"
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- source_model: LunaticPython161/CyberWitch-7B
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positive_prompts:
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- "solve"
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- "count"
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- "math"
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- "mathematics"
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- "algorithm"
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- "cypher"
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- "cybersecurity"
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- "penetration testing"
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- "red team"
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- "blue team"
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- "hacking"
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model-00001-of-00003.safetensors
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size 9919830088
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model-00002-of-00003.safetensors
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model.safetensors.index.json
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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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