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Browse files- README.md +63 -0
- config.json +27 -0
- mergekit_config.yml +17 -0
- model-00001-of-00007.safetensors +3 -0
- model-00002-of-00007.safetensors +3 -0
- model-00003-of-00007.safetensors +3 -0
- model-00004-of-00007.safetensors +3 -0
- model-00005-of-00007.safetensors +3 -0
- model-00006-of-00007.safetensors +3 -0
- model-00007-of-00007.safetensors +3 -0
- 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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- cognitivecomputations/dolphin-llama2-7b
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- Tensoic/Llama-2-openhermes
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base_model:
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- cognitivecomputations/dolphin-llama2-7b
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- Tensoic/Llama-2-openhermes
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---
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# DolphinHermesLlama-7B-SLERP
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DolphinHermesLlama-7B-SLERP is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [cognitivecomputations/dolphin-llama2-7b](https://huggingface.co/cognitivecomputations/dolphin-llama2-7b)
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* [Tensoic/Llama-2-openhermes](https://huggingface.co/Tensoic/Llama-2-openhermes)
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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: cognitivecomputations/dolphin-llama2-7b
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layer_range: [0, 32]
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- model: Tensoic/Llama-2-openhermes
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layer_range: [0, 32]
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merge_method: slerp
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base_model: Tensoic/Llama-2-openhermes
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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 = "sethuiyer/DolphinHermesLlama-7B-SLERP"
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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": "Tensoic/Llama-2-openhermes",
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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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"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": 11008,
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"max_position_embeddings": 4096,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 32,
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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": "4.35.2",
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"use_cache": false,
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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: cognitivecomputations/dolphin-llama2-7b
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layer_range: [0, 32]
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- model: Tensoic/Llama-2-openhermes
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layer_range: [0, 32]
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merge_method: slerp
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base_model: Tensoic/Llama-2-openhermes
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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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"lstrip": false,
|
16 |
+
"normalized": false,
|
17 |
+
"rstrip": false,
|
18 |
+
"single_word": false,
|
19 |
+
"special": true
|
20 |
+
},
|
21 |
+
"2": {
|
22 |
+
"content": "</s>",
|
23 |
+
"lstrip": false,
|
24 |
+
"normalized": false,
|
25 |
+
"rstrip": false,
|
26 |
+
"single_word": false,
|
27 |
+
"special": true
|
28 |
+
}
|
29 |
+
},
|
30 |
+
"bos_token": "<s>",
|
31 |
+
"clean_up_tokenization_spaces": false,
|
32 |
+
"eos_token": "</s>",
|
33 |
+
"legacy": false,
|
34 |
+
"model_max_length": 1000000000000000019884624838656,
|
35 |
+
"pad_token": "</s>",
|
36 |
+
"padding_side": "right",
|
37 |
+
"sp_model_kwargs": {},
|
38 |
+
"spaces_between_special_tokens": false,
|
39 |
+
"tokenizer_class": "LlamaTokenizer",
|
40 |
+
"trust_remote_code": false,
|
41 |
+
"unk_token": "<unk>",
|
42 |
+
"use_default_system_prompt": true,
|
43 |
+
"use_fast": true
|
44 |
+
}
|