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- added_tokens.json +24 -0
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README.md
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---
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license: other
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license_name: qwen
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license_link: https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE
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language:
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- en
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pipeline_tag: text-generation
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base_model:
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tags:
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# Qwen-122B
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Qwen-122B is a [Qwen/Qwen-72B](https://huggingface.co/Qwen/Qwen-72B) self-merge made with [MergeKit](https://github.com/arcee-ai/mergekit/tree/main).
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It was inspired by large merges like:
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- [alpindale/goliath-120b](https://huggingface.co/alpindale/goliath-120b)
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- [nsfwthrowitaway69/Venus-120b-v1.0](https://huggingface.co/nsfwthrowitaway69/Venus-120b-v1.0)
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- [cognitivecomputations/MegaDolphin-120b](https://huggingface.co/cognitivecomputations/MegaDolphin-120b)
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- [wolfram/miquliz-120b-v2.0](https://huggingface.co/wolfram/miquliz-120b-v2.0)
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- [mlabonne/Meta-Llama-3-120B-Instruct](https://huggingface.co/mlabonne/Meta-Llama-3-120B-Instruct)
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## 🔍 Applications
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This model is recommended for creative writing tasks. It uses the Qwen chat template with a default context window of 8K (can be extended with rope theta).
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The model is generally quite creative and has a good writing style. It may occasionally output typos and show a preference for uppercase text.
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## ⚡ Quantized models
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* **mlx**: [Link to mlx model]
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This model has yet to be thoroughly evaluated. It is expected to excel in creative writing but may have limitations in other tasks. Use it with caution and don't expect it to outperform state-of-the-art models outside of specific creative use cases.
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*
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* Comparisons with other large language models in various applications
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* Community feedback and use cases
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```yaml
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slices:
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- sources:
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- layer_range: [0, 20]
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model: Qwen/
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- sources:
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- layer_range: [10, 30]
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model: Qwen/
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- layer_range: [20, 40]
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model: Qwen/
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- layer_range: [30, 50]
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model: Qwen/
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- sources:
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- layer_range: [40, 60]
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model: Qwen/
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- layer_range: [50, 70]
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model: Qwen/
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- sources:
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- layer_range: [60, 80]
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model: Qwen/
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merge_method: passthrough
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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 = "path/to/Qwen-122B"
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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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base_model:
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- Qwen/Qwen2.5-72B-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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# merged
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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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* [Qwen/Qwen2.5-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-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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dtype: bfloat16
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merge_method: passthrough
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slices:
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- sources:
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- layer_range: [0, 20]
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model: Qwen/Qwen2.5-72B-Instruct
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- sources:
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- layer_range: [10, 30]
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model: Qwen/Qwen2.5-72B-Instruct
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- sources:
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- layer_range: [20, 40]
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model: Qwen/Qwen2.5-72B-Instruct
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- layer_range: [30, 50]
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model: Qwen/Qwen2.5-72B-Instruct
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- sources:
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- layer_range: [40, 60]
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model: Qwen/Qwen2.5-72B-Instruct
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- sources:
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- layer_range: [50, 70]
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model: Qwen/Qwen2.5-72B-Instruct
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- sources:
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- layer_range: [60, 80]
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model: Qwen/Qwen2.5-72B-Instruct
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```
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added_tokens.json
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{
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"</tool_call>": 151658,
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"<tool_call>": 151657,
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"<|box_end|>": 151649,
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"<|box_start|>": 151648,
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"<|endoftext|>": 151643,
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"<|file_sep|>": 151664,
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"<|fim_middle|>": 151660,
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"<|fim_pad|>": 151662,
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"<|fim_prefix|>": 151659,
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"<|fim_suffix|>": 151661,
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"<|im_end|>": 151645,
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"<|im_start|>": 151644,
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"<|image_pad|>": 151655,
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"<|object_ref_end|>": 151647,
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"<|object_ref_start|>": 151646,
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"<|quad_end|>": 151651,
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"<|quad_start|>": 151650,
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"<|repo_name|>": 151663,
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"<|video_pad|>": 151656,
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"<|vision_end|>": 151653,
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"<|vision_pad|>": 151654,
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"<|vision_start|>": 151652
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}
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config.json
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{
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"_name_or_path": "Qwen/Qwen2.5-72B-Instruct",
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"eos_token_id": 151645,
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"hidden_act": "silu",
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"hidden_size": 8192,
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"initializer_range": 0.02,
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"intermediate_size": 29568,
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"max_position_embeddings": 32768,
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"max_window_layers": 70,
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"model_type": "qwen2",
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"num_attention_heads": 64,
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"num_hidden_layers": 140,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-06,
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"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.44.2",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 152064
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}
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mergekit_config.yml
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dtype: bfloat16
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merge_method: passthrough
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slices:
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- sources:
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- layer_range: [0, 20]
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model: Qwen/Qwen2.5-72B-Instruct
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- sources:
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- layer_range: [10, 30]
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model: Qwen/Qwen2.5-72B-Instruct
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- sources:
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- layer_range: [20, 40]
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model: Qwen/Qwen2.5-72B-Instruct
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- sources:
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- layer_range: [30, 50]
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model: Qwen/Qwen2.5-72B-Instruct
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- sources:
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- layer_range: [40, 60]
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model: Qwen/Qwen2.5-72B-Instruct
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- sources:
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- layer_range: [50, 70]
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model: Qwen/Qwen2.5-72B-Instruct
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- sources:
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- layer_range: [60, 80]
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model: Qwen/Qwen2.5-72B-Instruct
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merges.txt
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