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Browse files- .gitattributes +1 -34
- README.md +70 -0
- config.json +35 -0
- mergekit_moe_config.yml +18 -0
- merges.txt +0 -0
- model-00001-of-00001.safetensors +3 -0
- model.safetensors.index.json +1 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer_config.json +38 -0
- vocab.json +0 -0
.gitattributes
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model-00001-of-00001.safetensors filter=lfs diff=lfs merge=lfs -text
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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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- merge
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- mergekit
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- lazymergekit
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- ahxt/LiteLlama-460M-1T
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- ahxt/LiteLlama-460M-1T
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- ahxt/LiteLlama-460M-1T
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- ahxt/LiteLlama-460M-1T
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- ahxt/LiteLlama-460M-1T
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- ahxt/LiteLlama-460M-1T
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---
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# KnowledgeNinja-LiteLlama-460Mx6MoE-1T
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KnowledgeNinja-LiteLlama-460Mx6MoE-1T 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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* [ahxt/LiteLlama-460M-1T](https://huggingface.co/ahxt/LiteLlama-460M-1T)
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* [ahxt/LiteLlama-460M-1T](https://huggingface.co/ahxt/LiteLlama-460M-1T)
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* [ahxt/LiteLlama-460M-1T](https://huggingface.co/ahxt/LiteLlama-460M-1T)
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* [ahxt/LiteLlama-460M-1T](https://huggingface.co/ahxt/LiteLlama-460M-1T)
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* [ahxt/LiteLlama-460M-1T](https://huggingface.co/ahxt/LiteLlama-460M-1T)
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* [ahxt/LiteLlama-460M-1T](https://huggingface.co/ahxt/LiteLlama-460M-1T)
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## 🧩 Configuration
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```yaml
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base_model: ahxt/LiteLlama-460M-1T
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gate_mode: hidden
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dtype: bfloat16
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experts:
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- source_model: ahxt/LiteLlama-460M-1T
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positive_prompts: ["Accounting"]
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- source_model: ahxt/LiteLlama-460M-1T
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positive_prompts: ["Finance"]
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- source_model: ahxt/LiteLlama-460M-1T
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positive_prompts: ["Strategy"]
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- source_model: ahxt/LiteLlama-460M-1T
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positive_prompts: ["Marketing"]
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- source_model: ahxt/LiteLlama-460M-1T
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positive_prompts: ["Organizational Behaviour"]
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- source_model: ahxt/LiteLlama-460M-1T
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positive_prompts: ["Economics"]
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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 = "AkiGogikar/KnowledgeNinja-LiteLlama-460Mx6MoE-1T"
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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": "ahxt/LiteLlama-460M-1T",
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"architectures": [
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"MixtralForCausalLM"
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],
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"attention_bias": false,
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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": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"layernorm_epsilon": 1e-05,
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"max_position_embeddings": 1024,
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"model_type": "mixtral",
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"num_attention_heads": 16,
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"num_experts_per_tok": 2,
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"num_hidden_layers": 24,
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"num_key_value_heads": 2,
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"num_local_experts": 6,
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"output_router_logits": false,
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"pad_token_id": 0,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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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": "4.36.2",
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"use_cache": true,
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"vocab_size": 50304
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}
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mergekit_moe_config.yml
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base_model: ahxt/LiteLlama-460M-1T
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gate_mode: hidden
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dtype: bfloat16
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experts:
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- source_model: ahxt/LiteLlama-460M-1T
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positive_prompts: ["Accounting"]
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- source_model: ahxt/LiteLlama-460M-1T
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positive_prompts: ["Finance"]
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- source_model: ahxt/LiteLlama-460M-1T
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positive_prompts: ["Strategy"]
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- source_model: ahxt/LiteLlama-460M-1T
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positive_prompts: ["Marketing"]
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- source_model: ahxt/LiteLlama-460M-1T
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positive_prompts: ["Organizational Behaviour"]
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- source_model: ahxt/LiteLlama-460M-1T
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positive_prompts: ["Economics"]
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merges.txt
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model-00001-of-00001.safetensors
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size 3943641472
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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_config.json
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vocab.json
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