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Browse files- README.md +13 -51
- config.json +1 -1
- mergekit_config.yml +1 -1
- model-00427-of-00481.safetensors +3 -0
- model-00433-of-00481.safetensors +3 -0
- tokenizer_config.json +1 -1
README.md
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---
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base_model:
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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# 🦙✨ BigLlama-3.1-1T-Instruct
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/ywomdgvQYP9cpr-PH1nf7.png)
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<center>🦙⛰️ <i><a href="https://huggingface.co/mlabonne/BigLlama-3.1-681B-Instruct">mlabonne/BigLlama-3.1-681B-Instruct</a></i></center>
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This is the direct successor of [Meta-Llama-3-120B-Instruct](https://huggingface.co/mlabonne/Meta-Llama-3-120B-Instruct), a self-merge of Llama 3 70B that produced a decent 120B model for tasks like creative writing.
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I tweaked the range of duplicated layers to hopefully make a sensible model. Use it at your own risk!
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## 🔍 Applications
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##
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```yaml
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slices:
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model: mlabonne/BigLlama-3.1-681B-Instruct
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merge_method: passthrough
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dtype: bfloat16
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```
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Here is the code I've used to generate the config and calculate the number of layers/parameters after passthrough:
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```python
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def generate_yaml_config(range_size, total_layers, nb_parameters):
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new_size = total_layers + total_layers - range_size
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new_param = (nb_parameters / total_layers) * new_size
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print(f"New size = {new_size} layers")
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print(f"New parameters = {new_param:.2f}B")
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yaml_str = "slices:\n"
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for i in range(0, round(total_layers - range_size + 1), range_size // 2):
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start = i
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end = min(start + range_size, total_layers)
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yaml_str += f"- sources:\n"
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yaml_str += f" - layer_range: [{start}, {end}]\n"
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yaml_str += f" model: meta-llama/Meta-Llama-3.1-405B-Instruct\n"
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yaml_str += "dtype: bfloat16\n"
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print(yaml_str)
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return new_size, new_param
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# Example usage
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new_size, new_param = generate_yaml_config(42, 126, 410)
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new_size, new_param = generate_yaml_config(105, new_size, new_param)
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```
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---
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base_model:
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- mlabonne/BigLlama-3.1-681B-Instruct
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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# BigLlama-3.1-1T-Instruct
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the passthrough merge method.
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### Models Merged
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The following models were included in the merge:
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* [mlabonne/BigLlama-3.1-681B-Instruct](https://huggingface.co/mlabonne/BigLlama-3.1-681B-Instruct)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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slices:
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model: mlabonne/BigLlama-3.1-681B-Instruct
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merge_method: passthrough
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dtype: bfloat16
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```
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config.json
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.
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"use_cache": true,
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"vocab_size": 128256
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}
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.44.0",
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"use_cache": true,
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"vocab_size": 128256
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}
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mergekit_config.yml
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- layer_range: [104, 209]
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model: mlabonne/BigLlama-3.1-681B-Instruct
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merge_method: passthrough
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dtype: bfloat16
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- layer_range: [104, 209]
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model: mlabonne/BigLlama-3.1-681B-Instruct
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merge_method: passthrough
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dtype: bfloat16
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model-00427-of-00481.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:a7a93419dcc4485d05ba631b082c8a5c9ecd819ac1beb63db5b841ebc1137674
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size 4697687008
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model-00433-of-00481.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c5decda5f7406f249ad0489d85729d204f66ad75ccdcb9f5f23ec3b5b88f0862
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size 4697687008
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tokenizer_config.json
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],
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"model_max_length": 131072,
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"tokenizer_class": "PreTrainedTokenizerFast"
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}
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],
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"model_max_length": 131072,
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"tokenizer_class": "PreTrainedTokenizerFast"
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}
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