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Model: Q-bert/MetaMath-Cybertron-Starling
Source: Original Platform

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README.md

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+---
+license: cc-by-nc-4.0
+datasets:
+- meta-math/MetaMathQA
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- Math
+- merge
+base_model:
+- Q-bert/MetaMath-Cybertron
+- berkeley-nest/Starling-LM-7B-alpha
+---
+
+## MetaMath-Cybertron-Starling
+
+
+Merge [Q-bert/MetaMath-Cybertron](https://huggingface.co/Q-bert/MetaMath-Cybertron) and [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha) using slerp merge.
+
+You can use ChatML format.
+
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [Here](https://huggingface.co/datasets/open-llm-leaderboard/results/blob/main/Q-bert/MetaMath-Cybertron-Starling/results_2023-12-07T21-59-56.458563.json)
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 71.35               |
+| ARC (25-shot)         | 67.75               |
+| HellaSwag (10-shot)   | 86.23               |
+| MMLU (5-shot)         | 65.24               |
+| TruthfulQA (0-shot)   | 55.94               |
+| Winogrande (5-shot)   | 81.45               |
+| GSM8K (5-shot)        | 71.49               |

config.json

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+{
+  "_name_or_path": "Q-bert/MetaMath-Cybertron",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.35.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

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special_tokens_map.json

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tokenizer_config.json

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+{
+  "added_tokens_decoder": {
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+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": true
+}