Abdulhanan2006
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Browse files- README.md +43 -0
- config.json +29 -0
- mergekit_config.yml +17 -0
- model-00001-of-00028.safetensors +3 -0
- model-00002-of-00028.safetensors +3 -0
- model-00003-of-00028.safetensors +3 -0
- model-00004-of-00028.safetensors +3 -0
- model-00005-of-00028.safetensors +3 -0
- model-00006-of-00028.safetensors +3 -0
- model-00007-of-00028.safetensors +3 -0
- model-00008-of-00028.safetensors +3 -0
- model-00009-of-00028.safetensors +3 -0
- model-00010-of-00028.safetensors +3 -0
- model-00011-of-00028.safetensors +3 -0
- model-00012-of-00028.safetensors +3 -0
- model-00013-of-00028.safetensors +3 -0
- model-00014-of-00028.safetensors +3 -0
- model-00015-of-00028.safetensors +3 -0
- model-00016-of-00028.safetensors +3 -0
- model-00017-of-00028.safetensors +3 -0
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- model.safetensors.index.json +1 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +44 -0
README.md
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---
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tags:
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- merge
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- mergekit
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- lazymergekit
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- PygmalionAI/pygmalion-2-13b
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- elinas/chronos-13b-v2
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base_model:
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- PygmalionAI/pygmalion-2-13b
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- elinas/chronos-13b-v2
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---
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# LogicLumina-L3-13B
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LogicLumina-L3-13B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [PygmalionAI/pygmalion-2-13b](https://huggingface.co/PygmalionAI/pygmalion-2-13b)
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* [elinas/chronos-13b-v2](https://huggingface.co/elinas/chronos-13b-v2)
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## 🧩 Configuration
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## 💻 Usage
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```python
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!pip install -qU transformers 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 = "Abdulhanan2006/LogicLumina-L3-13B"
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messages = [{"role": "user", "content": "What is a large language model?"}]
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tokenizer = AutoTokenizer.from_pretrained(model)
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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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": "PygmalionAI/pygmalion-2-13b",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"badwordsids": "[[29961], [14352], [24630], [29962], [11759], [15974], [5519], [25473], [18899], [25901], [7110], [9341], [13531], [518], [9310], [2636], [3366], [21069], [11970], [23098], [16733], [21298], [18173], [10846], [3816], [28513], [15625], [23192], [28166], [10062], [1385], [11724], [3108], [15555], [10834], [10370], [14330], [1822], [12436], [5262], [17094], [10725], [17077], [11424], [4197], [24406], [13359], [17531], [24566], [23076], [4514], [13192], [19942], [16261], [7072], [6024], [1402], [1839], [2033], [13970], [850], [5913], [28895], [5387], [8308], [24927], [5691], [12940], [19997], [18959], [11287], [16862], [4638], [22322], [29861], [21251], [14704], [17548], [12452], [17288], [23160], [24960], [8219], [18024], [5539], [7464], [27865], [29588], [20068], [19660], [27706], [22896], [24264], [12258], [2314], [4400], [5586], [12622], [6796], [7226], [21939], [18456], [14178], [21540], [21945], [14664], [16215], [10338], [17361], [7503], [13769], [26073], [9601], [26909], [7961], [8999], [20840], [16272], [21545], [3199], [10514], [5159], [22689], [6525], [20526], [27077], [18017]]",
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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": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 13824,
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"max_position_embeddings": 4096,
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"model_type": "llama",
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"num_attention_heads": 40,
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"num_hidden_layers": 40,
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"num_key_value_heads": 40,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.38.2",
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"use_cache": true,
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"vocab_size": 32000
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}
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mergekit_config.yml
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slices:
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- sources:
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- model: PygmalionAI/pygmalion-2-13b
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layer_range: [0, 40]
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- model: elinas/chronos-13b-v2
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layer_range: [0, 40]
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merge_method: slerp
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base_model: PygmalionAI/pygmalion-2-13b
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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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tokenizer.json
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tokenizer.model
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tokenizer_config.json
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