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Browse files- README.md +61 -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 +40 -0
README.md
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---
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license: apache-2.0
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tags:
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- merge
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- mergekit
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- lazymergekit
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- OpenPipe/mistral-ft-optimized-1218
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- mlabonne/NeuralHermes-2.5-Mistral-7B
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---
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# Fulcrum_Nova
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Fulcrum_Nova is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [OpenPipe/mistral-ft-optimized-1218](https://huggingface.co/OpenPipe/mistral-ft-optimized-1218)
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* [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-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: 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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```
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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 = "Spanicin/Fulcrum_Nova"
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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": "4.35.2",
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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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tokenizer.json
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4 |
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5 |
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6 |
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7 |
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8 |
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9 |
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10 |
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},
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11 |
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12 |
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13 |
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14 |
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15 |
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16 |
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17 |
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18 |
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},
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19 |
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20 |
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"content": "</s>",
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21 |
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22 |
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23 |
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24 |
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25 |
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26 |
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}
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27 |
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},
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28 |
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29 |
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30 |
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31 |
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"eos_token": "</s>",
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32 |
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33 |
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34 |
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35 |
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36 |
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37 |
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"tokenizer_class": "LlamaTokenizer",
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38 |
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"unk_token": "<unk>",
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39 |
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|
40 |
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}
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