Crystalcareai
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Browse files- README.md +78 -0
- added_tokens.json +4 -0
- config.json +30 -0
- mergekit_moe_config.yml +30 -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 +61 -0
README.md
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---
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license: mit
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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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- Open-Orca/Mistral-7B-OpenOrca
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- Crystalcareai/Evol-Mistral
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base_model:
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- Open-Orca/Mistral-7B-OpenOrca
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- Crystalcareai/Evol-Mistral
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---
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# Evolorxa-14b
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Evolorxa-14b 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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* [Open-Orca/Mistral-7B-OpenOrca](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca)
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* [Crystalcareai/Evol-Mistral](https://huggingface.co/Crystalcareai/Evol-Mistral)
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## 🧩 Configuration
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```yaml
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slices:
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- sources:
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- model: Open-Orca/Mistral-7B-OpenOrca
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layer_range: [0, 32]
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- model: Crystalcareai/Evol-Mistral
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layer_range: [0, 32]
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merge_method: slerp
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base_model: Open-Orca/Mistral-7B-OpenOrca
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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experts:
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- source_model: Open-Orca/Mistral-7B-OpenOrca
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positive_prompts:
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- "chat"
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- "reasoning"
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- "Why would"
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- "explain"
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- source_model: Crystalcareai/Evol-Mistral
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positive_prompts:
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- "instruction"
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- "create a"
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- "You must"
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- "Your job"
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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 = "Crystalcareai/Evolorxa-14b"
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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_end|>": 32000,
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"<|im_start|>": 32001
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}
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config.json
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{
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"_name_or_path": "Open-Orca/Mistral-7B-OpenOrca",
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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": 32000,
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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": "4.36.2",
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"use_cache": true,
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"vocab_size": 32002
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}
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mergekit_moe_config.yml
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slices:
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- sources:
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- model: Open-Orca/Mistral-7B-OpenOrca
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layer_range: [0, 32]
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- model: Crystalcareai/Evol-Mistral
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layer_range: [0, 32]
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merge_method: slerp
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base_model: Open-Orca/Mistral-7B-OpenOrca
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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experts:
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- source_model: Open-Orca/Mistral-7B-OpenOrca
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+
positive_prompts:
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- "chat"
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+
- "reasoning"
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- "Why would"
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- "explain"
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- source_model: Crystalcareai/Evol-Mistral
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positive_prompts:
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- "instruction"
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- "create a"
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- "You must"
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- "Your job"
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model-00001-of-00003.safetensors
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size 9919846472
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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
ADDED
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{
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|
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tokenizer.json
ADDED
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tokenizer.model
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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size 493443
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tokenizer_config.json
ADDED
@@ -0,0 +1,61 @@
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},
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}
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},
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"additional_special_tokens": [],
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"bos_token": "<s>",
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"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
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