nagayama0706
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Browse files- README.md +63 -0
- config.json +26 -0
- mergekit_config.yml +17 -0
- model-00001-of-00008.safetensors +3 -0
- model-00002-of-00008.safetensors +3 -0
- model-00003-of-00008.safetensors +3 -0
- model-00004-of-00008.safetensors +3 -0
- model-00005-of-00008.safetensors +3 -0
- model-00006-of-00008.safetensors +3 -0
- model-00007-of-00008.safetensors +3 -0
- model-00008-of-00008.safetensors +3 -0
- model.safetensors.index.json +1 -0
- special_tokens_map.json +23 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +42 -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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- huggingface/CodeBERTa-language-id
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- Sharathhebbar24/code_gpt2
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base_model:
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- huggingface/CodeBERTa-language-id
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- Sharathhebbar24/code_gpt2
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---
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# test_merge4_
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test_merge4_ is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [huggingface/CodeBERTa-language-id](https://huggingface.co/huggingface/CodeBERTa-language-id)
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* [Sharathhebbar24/code_gpt2](https://huggingface.co/Sharathhebbar24/code_gpt2)
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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: huggingface/CodeBERTa-language-id
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layer_range: [0, 32]
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- model: Sharathhebbar24/code_gpt2
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layer_range: [0, 32]
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merge_method: slerp
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base_model: huggingface/CodeBERTa-language-id
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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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```
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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 = "nagayama0706/test_merge4_"
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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": "OpenPipe/mistral-ft-optimized-1218",
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"architectures": [
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"MistralForCausalLM"
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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": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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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: OpenPipe/mistral-ft-optimized-1218
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layer_range: [0, 32]
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- model: mlabonne/NeuralHermes-2.5-Mistral-7B
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layer_range: [0, 32]
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merge_method: slerp
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base_model: OpenPipe/mistral-ft-optimized-1218
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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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2 |
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|
3 |
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|
4 |
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"added_tokens_decoder": {
|
5 |
+
"0": {
|
6 |
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"content": "<unk>",
|
7 |
+
"lstrip": false,
|
8 |
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|
9 |
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|
10 |
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"single_word": false,
|
11 |
+
"special": true
|
12 |
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},
|
13 |
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"1": {
|
14 |
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"content": "<s>",
|
15 |
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"lstrip": false,
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16 |
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|
17 |
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18 |
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"single_word": false,
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19 |
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"special": true
|
20 |
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},
|
21 |
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"2": {
|
22 |
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"content": "</s>",
|
23 |
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"lstrip": false,
|
24 |
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"normalized": false,
|
25 |
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|
26 |
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"single_word": false,
|
27 |
+
"special": true
|
28 |
+
}
|
29 |
+
},
|
30 |
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"additional_special_tokens": [],
|
31 |
+
"bos_token": "<s>",
|
32 |
+
"clean_up_tokenization_spaces": false,
|
33 |
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"eos_token": "</s>",
|
34 |
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"legacy": true,
|
35 |
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"model_max_length": 1000000000000000019884624838656,
|
36 |
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|
37 |
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"sp_model_kwargs": {},
|
38 |
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"spaces_between_special_tokens": false,
|
39 |
+
"tokenizer_class": "LlamaTokenizer",
|
40 |
+
"unk_token": "<unk>",
|
41 |
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"use_default_system_prompt": false
|
42 |
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}
|