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Model: DeepAuto-AI/ldm_soup_Llama-3.1-8B-Inst
Source: Original Platform

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README.md

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+---
+library_name: transformers
+model-index:
+- name: ldm_soup_Llama-3.1-8B-Inst
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: HuggingFaceH4/ifeval
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 80.33
+      name: strict accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: BBH
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 31.1
+      name: normalized accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: hendrycks/competition_math
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 11.56
+      name: exact match
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 5.26
+      name: acc_norm
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MuSR (0-shot)
+      type: TAUR-Lab/MuSR
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 11.52
+      name: acc_norm
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU-PRO (5-shot)
+      type: TIGER-Lab/MMLU-Pro
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 32.07
+      name: accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst
+      name: Open LLM Leaderboard
+license: apache-2.0
+language:
+- en
+base_model:
+- meta-llama/Llama-3.1-8B-Instruct
+---
+
+# Model Card for DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst
+
+Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in
+- compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+
+## Overview
+
+
+**DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst** is developed by **deepAuto.ai** and builds upon the **VAGOsolutions/Llama-3.1-SauerkrautLM-8B-Instruct** model. Our approach leverages the base model’s pretrained weights and optimizes them for the **Winogrande** and **ARC-Challenge** datasets by training a latent diffusion model on the pretrained weights.
+
+Through this process, we learn the distribution of the base model's weight space, enabling us to explore optimal configurations. We then sample multiple sets of weights, using the **model-soup averaging technique** to identify the best-performing weights for both datasets. These weights are merged using linear interpolation to create the final model weights for **DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst**.
+
+This approach has led to improved performance on previously unseen leaderboard tasks, all without any additional task-specific training.
+
+The work is currently in progress
+
+
+
+
+## References
+<a href="https://arxiv.org/abs/2402.18153" target="_blank">Diffusion-Based Neural Network Weights Generation</a>
+
+
+
+## Evaluation
+
+
+
+### Results
+
+
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_DeepAutoAI__ldm_soup_Llama-3.1-8B-Inst)
+
+|      Metric       |Value|
+|-------------------|----:|
+|Avg.               |28.64|
+|IFEval (0-Shot)    |80.33|
+|BBH (3-Shot)       |31.10|
+|MATH Lvl 5 (4-Shot)|11.56|
+|GPQA (0-shot)      | 5.26|
+|MuSR (0-shot)      |11.52|
+|MMLU-PRO (5-shot)  |32.07|

config.json

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+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": [
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+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
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+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.44.2",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 128000,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "transformers_version": "4.44.2"
+}

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