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Model: Weyaxi/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp Source: Original Platform
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README.md
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---
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license: apache-2.0
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model-index:
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- name: MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 64.59
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name: normalized accuracy
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- type: acc_norm
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value: 64.59
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name: normalized accuracy
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source:
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url: >-
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 85.39
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name: normalized accuracy
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- type: acc_norm
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value: 85.39
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name: normalized accuracy
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source:
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url: >-
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 64.27
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name: accuracy
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- type: acc
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value: 64.27
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name: accuracy
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source:
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url: >-
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 55.14
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- type: mc2
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value: 55.14
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source:
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url: >-
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 79.64
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name: accuracy
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- type: acc
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value: 79.64
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name: accuracy
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source:
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url: >-
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 71.65
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name: accuracy
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- type: acc
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value: 71.65
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name: accuracy
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source:
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url: >-
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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name: Open LLM Leaderboard
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tags:
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- merge
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---
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# MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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This is the model for MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp. I used [mergekit](https://github.com/cg123/mergekit) to merge models.
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# Yaml Config to reproduce
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```yaml
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slices:
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- sources:
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- model: meta-math/MetaMath-Mistral-7B
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layer_range: [0, 32]
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- model: PulsarAI/OpenHermes-2.5-neural-chat-v3-3-Slerp
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layer_range: [0, 32]
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merge_method: slerp
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base_model: mistralai/Mistral-7B-v0.1
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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 # fallback for rest of tensors
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dtype: bfloat16
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```
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config.json
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{
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"_name_or_path": "mistralai/Mistral-7B-v0.1",
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"architectures": [
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"MistralForCausalLM"
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],
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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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model-00001-of-00002.safetensors
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model-00001-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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size 9942981696
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special_tokens_map.json
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special_tokens_map.json
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{
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}
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tokenizer.json
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tokenizer.json
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tokenizer.model
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"eos_token": "</s>",
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"sp_model_kwargs": {},
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": "<unk>",
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"use_default_system_prompt": false
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}
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