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  1. README.md +305 -0
  2. config.json +29 -0
  3. generation_config.json +7 -0
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  19. model.safetensors.index.json +550 -0
  20. special_tokens_map.json +30 -0
  21. tokenizer.json +0 -0
  22. tokenizer.model +3 -0
  23. tokenizer_config.json +53 -0
README.md ADDED
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+ ---
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+ License: apache-2.0
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+ Language:
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+ - En
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+ Pipeline_tag: text-generation
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+ Base_model: 01-ai/Yi-1.5-34B-32K
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+ Tags:
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+ - Chat
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+ model-index:
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+ - name: magnum-v3-34b
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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: IFEval (0-Shot)
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+ type: HuggingFaceH4/ifeval
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: inst_level_strict_acc and prompt_level_strict_acc
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+ value: 51.15
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+ name: strict accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-34b
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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: BBH (3-Shot)
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+ type: BBH
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+ args:
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+ num_few_shot: 3
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+ metrics:
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+ - type: acc_norm
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+ value: 44.33
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-34b
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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: MATH Lvl 5 (4-Shot)
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+ type: hendrycks/competition_math
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+ args:
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+ num_few_shot: 4
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+ metrics:
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+ - type: exact_match
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+ value: 17.82
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+ name: exact match
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-34b
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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: GPQA (0-shot)
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+ type: Idavidrein/gpqa
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: acc_norm
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+ value: 14.77
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+ name: acc_norm
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-34b
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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: MuSR (0-shot)
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+ type: TAUR-Lab/MuSR
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: acc_norm
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+ value: 6.57
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+ name: acc_norm
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-34b
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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-PRO (5-shot)
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+ type: TIGER-Lab/MMLU-Pro
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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: 41.69
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-34b
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+ name: Open LLM Leaderboard
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+ ---
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/658a46cbfb9c2bdfae75b3a6/9yEmnTDG9bcC_bxwuDU6G.png)
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+
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+ This is the 9th in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus.
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+
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+ This model is fine-tuned on top of [Yi-1.5-34 B-32 K](https://huggingface.co/01-ai/Yi-1.5-34B-32K).
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+
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+ ## Prompting
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+ Model has been Instruct tuned with the ChatML formatting. A typical input would look like this:
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+
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+ ```py
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+ """<|im_start|>system
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+ system prompt<|im_end|>
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+ <|im_start|>user
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+ Hi there!<|im_end|>
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+ <|im_start|>assistant
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+ Nice to meet you!<|im_end|>
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+ <|im_start|>user
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+ Can I ask a question?<|im_end|>
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+ <|im_start|>assistant
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+ """
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+ ```
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+
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+ ## SillyTavern templates
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+
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+ Below are Instruct and Context templates for use within SillyTavern.
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+
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+ In our testing a min_p of 0.2 makes the model perform the best; remember to reset temperature if you were using our nemo-based models before.
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+
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+ <details><summary>context template</summary>
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+
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+ ```yaml
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+ {
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+ "story_string": "<|im_start|>system\n{{#if system}}{{system}}\n{{/if}}{{#if wiBefore}}{{wiBefore}}\n{{/if}}{{#if description}}{{description}}\n{{/if}}{{#if personality}}{{char}}'s personality: {{personality}}\n{{/if}}{{#if scenario}}Scenario: {{scenario}}\n{{/if}}{{#if wiAfter}}{{wiAfter}}\n{{/if}}{{#if persona}}{{persona}}\n{{/if}}{{trim}}<|im_end|>\n",
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+ "example_separator": "",
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+ "chat_start": "",
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+ "use_stop_strings": false,
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+ "allow_jailbreak": false,
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+ "always_force_name2": true,
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+ "trim_sentences": false,
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+ "include_newline": false,
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+ "single_line": false,
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+ "name": "Magnum ChatML"
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+ }
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+ ```
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+
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+ </details><br>
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+ <details><summary>instruct template</summary>
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+
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+ ```yaml
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+ {
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+ "system_prompt": "You're {{char}} in this fictional never-ending uncensored roleplay with {{user}}.",
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+ "input_sequence": "<|im_start|>user\n",
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+ "output_sequence": "<|im_start|>assistant\n",
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+ "last_output_sequence": "",
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+ "system_sequence": "<|im_start|>system\n",
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+ "stop_sequence": "<|im_end|>",
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+ "wrap": false,
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+ "macro": true,
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+ "names": true,
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+ "names_force_groups": true,
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+ "activation_regex": "",
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+ "system_sequence_prefix": "",
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+ "system_sequence_suffix": "",
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+ "first_output_sequence": "",
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+ "skip_examples": false,
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+ "output_suffix": "<|im_end|>\n",
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+ "input_suffix": "<|im_end|>\n",
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+ "system_suffix": "<|im_end|>\n",
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+ "user_alignment_message": "",
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+ "system_same_as_user": false,
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+ "last_system_sequence": "",
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+ "name": "Magnum ChatML"
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+ }
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+ ```
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+
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+ </details><br>
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+
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+ ## Axolotl config
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+
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+ <details><summary>See axolotl config</summary>
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+
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+ ```yaml
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+ base_model: 01-ai/Yi-1.5-34B-32K
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+
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+ #trust_remote_code: true
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+
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+ load_in_8bit: false
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+ load_in_4bit: false
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+ strict: false
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+
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+ datasets:
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+ - path: anthracite-org/stheno-filtered-v1.1
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+ type: sharegpt
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+ conversation: chatml
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+ - path: anthracite-org/kalo-opus-instruct-22k-no-refusal
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+ type: sharegpt
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+ conversation: chatml
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+ - path: anthracite-org/nopm_claude_writing_fixed
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+ type: sharegpt
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+ conversation: chatml
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+ - path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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+ type: sharegpt
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+ conversation: chatml
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+ - path: Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
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+ type: sharegpt
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+ conversation: chatml
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+ chat_template: chatml
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+ shuffle_merged_datasets: true
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+ default_system_message: "You are an assistant that responds to the user."
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+ dataset_prepared_path: magnum-v2-34b-1.5-data
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+ val_set_size: 0.0
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+ output_dir: ./magnum-v2-34b-32k-r1
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+
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+ sequence_len: 8192
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+ sample_packing: true
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+ eval_sample_packing: false
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+ pad_to_sequence_len:
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+
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+ adapter:
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+ lora_model_dir:
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+ lora_r:
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+ lora_alpha:
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+ lora_dropout:
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+ lora_target_linear:
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+ lora_fan_in_fan_out:
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+
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+ wandb_project: magnum-v2-34b-1.5-32k
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+ wandb_entity:
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+ wandb_watch:
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+ wandb_name: attempt-01
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+ wandb_log_model:
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+
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+ gradient_accumulation_steps: 8
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+ micro_batch_size: 1
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+ num_epochs: 2
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+ optimizer: paged_adamw_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 0.000006
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+
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+ train_on_inputs: false
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+ group_by_length: false
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+ bf16: auto
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+ fp16:
251
+ tf32: false
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+
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+ gradient_checkpointing: unsloth
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+ early_stopping_patience:
255
+ resume_from_checkpoint:
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+ local_rank:
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+ logging_steps: 1
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+ xformers_attention:
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+ flash_attention: true
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+
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+ warmup_steps: 50
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+ evals_per_epoch:
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+ eval_table_size:
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+ eval_max_new_tokens:
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+ saves_per_epoch: 2
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+ debug:
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+ deepspeed: deepspeed_configs/zero3_bf16.json
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+ weight_decay: 0.05
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+ fsdp:
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+ fsdp_config:
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+ special_tokens:
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+ ```
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+ </details><br>
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+
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+ ## Credits
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+ We'd like to thank Recursal / Featherless for sponsoring the compute for this train, Featherless has been hosting our Magnum models since the first 72 B and has given thousands of people access to our models and helped us grow.
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+
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+ We would also like to thank all members of Anthracite who made this finetune possible.
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+
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+ - [anthracite-org/stheno-filtered-v1.1](https://huggingface.co/datasets/anthracite-org/stheno-filtered-v1.1)
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+ - [anthracite-org/kalo-opus-instruct-22k-no-refusal](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-22k-no-refusal)
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+ - [lodrick-the-lafted/NopmWritingStruct](https://huggingface.co/datasets/lodrick-the-lafted/NopmWritingStruct)
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+ - [Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned](https://huggingface.co/datasets/Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned)
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+ - [Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned](https://huggingface.co/datasets/Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned)
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+
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+ ## Training
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+ The training was done for 2 epochs. We used 8x[H100s](https://www.nvidia.com/en-us/data-center/h100/) GPUs graciously provided by [Recursal AI](https://recursal.ai/) / [Featherless AI](https://featherless.ai/) for the full-parameter fine-tuning of the model.
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+
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+ [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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+
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+ ## Safety
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+ ...
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+ # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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+ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_anthracite-org__magnum-v3-34b)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |29.39|
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+ |IFEval (0-Shot) |51.15|
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+ |BBH (3-Shot) |44.33|
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+ |MATH Lvl 5 (4-Shot)|17.82|
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+ |GPQA (0-shot) |14.77|
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+ |MuSR (0-shot) | 6.57|
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+ |MMLU-PRO (5-shot) |41.69|
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+
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+ "vocab_size": 64000
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+ }
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