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Browse files- README.md +63 -0
- added_tokens.json +7 -0
- config.json +29 -0
- mergekit_config.yml +20 -0
- model-00001-of-00004.safetensors +3 -0
- model-00002-of-00004.safetensors +3 -0
- model-00003-of-00004.safetensors +3 -0
- model-00004-of-00004.safetensors +3 -0
- model.safetensors.index.json +1 -0
- special_tokens_map.json +37 -0
- tokenizer.model +3 -0
- tokenizer_config.json +95 -0
README.md
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---
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base_model:
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- m-a-p/neo_7b
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tags:
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- merge
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- mergekit
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- lazymergekit
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- m-a-p/neo_7b
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---
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# Neo_7b-merge1
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Neo_7b-merge1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [m-a-p/neo_7b](https://huggingface.co/m-a-p/neo_7b)
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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: m-a-p/neo_7b
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layer_range: [0, 27] # 28 layers (0-27)
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merge_method: slerp
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base_model: m-a-p/neo_7b
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parameters:
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t:
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- filter: self_attn
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value: [0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75,
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0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75,
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0.5, 0.5, 0.5, 0.75]
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- filter: mlp
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value: [0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75,
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0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75,
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0.5, 0.5, 0.5, 0.75]
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- value: 0.5 # Default value for other components
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dtype: bfloat16
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output_path: ./merged_reduced_neo_7b
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```
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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 = "DewEfresh/Neo_7b-merge1"
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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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added_tokens.json
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{
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"<|CLS|>": 64000,
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"<|EOD|>": 64002,
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"<|MASK|>": 64003,
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"<|PAD|>": 64004,
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"<|SEP|>": 64001
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}
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config.json
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{
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"_name_or_path": "m-a-p/neo_7b",
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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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"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": 3072,
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"initializer_range": 0.02,
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"intermediate_size": 24576,
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"max_position_embeddings": 8192,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 16,
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"num_hidden_layers": 27,
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"num_key_value_heads": 16,
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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": "4.42.3",
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"use_cache": true,
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"vocab_size": 64256
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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: m-a-p/neo_7b
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layer_range: [0, 27] # 28 layers (0-27)
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merge_method: slerp
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base_model: m-a-p/neo_7b
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parameters:
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t:
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- filter: self_attn
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value: [0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75,
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0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75,
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0.5, 0.5, 0.5, 0.75]
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- filter: mlp
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value: [0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75,
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0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75,
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0.5, 0.5, 0.5, 0.75]
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- value: 0.5 # Default value for other components
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dtype: bfloat16
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output_path: ./merged_reduced_neo_7b
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model-00001-of-00004.safetensors
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model.safetensors.index.json
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special_tokens_map.json
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tokenizer.model
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"<|MASK|>",
|
75 |
+
"<|PAD|>"
|
76 |
+
],
|
77 |
+
"auto_map": {
|
78 |
+
"AutoTokenizer": [
|
79 |
+
"m-a-p/neo_7b--tokenization_neo.NEOTokenizer",
|
80 |
+
null
|
81 |
+
]
|
82 |
+
},
|
83 |
+
"bos_token": "<s>",
|
84 |
+
"chat_template": "{% set system_message = 'You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.\\n\\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don\\'t know the answer to a question, please don\\'t share false information.' %}{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% for message in messages %}{% set content = message['content'] %}{% if loop.index0 == 0 and system_message is defined %}{% set content = '<<SYS>>\\n' + system_message + '\\n<</SYS>>\\n\\n' + message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ '<s>' + '[INST] ' + content + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ content + '</s>' }}{% endif %}{% endfor %}",
|
85 |
+
"clean_up_tokenization_spaces": false,
|
86 |
+
"eos_token": "</s>",
|
87 |
+
"model_max_length": 4096,
|
88 |
+
"pad_token": "<unk>",
|
89 |
+
"padding_side": "right",
|
90 |
+
"sp_model_kwargs": {},
|
91 |
+
"split_special_tokens": false,
|
92 |
+
"tokenizer_class": "NEOTokenizer",
|
93 |
+
"unk_token": "<unk>",
|
94 |
+
"use_fast": false
|
95 |
+
}
|