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Model: TeeZee/NEBULA-XB-v1.0 Source: Original Platform
2026-04-25 18:08:01 +08:00
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--- a/README.md
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+---
+language:
+- en
+license: apache-2.0
+datasets:
+- Open-Orca/SlimOrca
+model-index:
+- name: NEBULA-XB-v1.0
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 56.66
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 81.78
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 60.98
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 44.03
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 77.66
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 0.0
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0
+      name: Open LLM Leaderboard
+---
+### TeeZee/NEBULA-XB-v1.03 ###
+
+Experiment, can DUS be taken one or more steps further?
+
+
+### Technical notes:
+- pretrained model v03 finetuned on 50k entries from SlimOrca dataset
+- 18 layers removed from both models of finetuned GALAXY-XB-v03
+- model has 108 layers (((48-12)*2)-18)*2 = 108
+- second step in scaling DUS procedure
+
+
+### To evaluate
+- model performance after merge, should be a little lover that GALAXY finetuned on 50k of slimorca
+# [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/details_TeeZee__NEBULA-XB-v1.0)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |53.52|
+|AI2 Reasoning Challenge (25-Shot)|56.66|
+|HellaSwag (10-Shot)              |81.78|
+|MMLU (5-Shot)                    |60.98|
+|TruthfulQA (0-shot)              |44.03|
+|Winogrande (5-shot)              |77.66|
+|GSM8k (5-shot)                   | 0.00|
+
--- a/config.json
+++ b/config.json
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+{
+  "_name_or_path": "F:\\merger\\mergekit\\GALAXY-XB-v0.3",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 108,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.35.2",
+  "use_cache": false,
+  "vocab_size": 32000
+}
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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "eos_token": {
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--- a/tokenizer.json
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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "single_word": false,
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+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "chat_template": "\n{{ bos_token }}\n{% for message in messages %}\n{% if message['from'] == 'system' %}\n{% if message['value']%}\n{{'### System:\n' + message['value']+'\n\n'}}\n{% endif %}{% elif message['from'] == 'human' %}\n{{'### User:\n' + message['value']+'\n\n'}}\n{% elif message['from'] == 'gpt' %}\n{{'### Assistant:\n'  + message['value'] + '</s>' + '\n'}}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '### Assistant:\n' }}\n{% endif %}\n{% endfor %}\n",
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": null,
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": true
+}