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+
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+ ---
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+
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+ language:
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+ - en
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+ license: agpl-3.0
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+ tags:
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+ - chat
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+ base_model:
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+ - nvidia/Mistral-NeMo-Minitron-8B-Base
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+ datasets:
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+ - anthracite-org/kalo-opus-instruct-22k-no-refusal
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+ - Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
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+ - lodrick-the-lafted/kalo-opus-instruct-3k-filtered
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+ - anthracite-org/nopm_claude_writing_fixed
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+ - Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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+ - anthracite-org/kalo_opus_misc_240827
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+ - anthracite-org/kalo_misc_part2
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+ License: agpl-3.0
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+ Language:
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+ - En
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+ Pipeline_tag: text-generation
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+ Base_model: nvidia/Mistral-NeMo-Minitron-8B-Base
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+ Tags:
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+ - Chat
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+ model-index:
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+ - name: Tor-8B
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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: 23.82
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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=Delta-Vector/Tor-8B
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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: 31.74
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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=Delta-Vector/Tor-8B
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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: 5.44
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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=Delta-Vector/Tor-8B
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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: 9.84
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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=Delta-Vector/Tor-8B
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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: 8.82
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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=Delta-Vector/Tor-8B
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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: 30.33
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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=Delta-Vector/Tor-8B
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+ name: Open LLM Leaderboard
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+
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+ ---
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+
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+ [![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
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+
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+
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+ # QuantFactory/Tor-8B-GGUF
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+ This is quantized version of [Delta-Vector/Tor-8B](https://huggingface.co/Delta-Vector/Tor-8B) created using llama.cpp
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+
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+ # Original Model Card
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+
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+
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+ ![](https://huggingface.co/Delta-Vector/Tor-8B/resolve/main/FinalTor8B.jpg)
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+
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+
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+
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+ An earlier checkpoint of [Darkens-8B](https://huggingface.co/Delta-Vector/Darkens-8B) using the same configuration that i felt was different enough from it's 4 epoch cousin to release, Finetuned ontop of the Prune/Distill NeMo 8B done by Nvidia, This model aims to have generally good prose and writing while not falling into claude-isms.
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+
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+
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+ # Quants
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+
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+ GGUF: https://huggingface.co/Delta-Vector/Tor-8B-GGUF
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+
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+ EXL2: https://huggingface.co/Delta-Vector/Tor-8B-EXL2
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+
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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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+ ## System Prompting
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+
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+ I would highly recommend using Sao10k's Euryale System prompt, But the "Roleplay Simple" system prompt provided within SillyTavern will work aswell.
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+
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+ ```
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+ Currently, your role is {{char}}, described in detail below. As {{char}}, continue the narrative exchange with {{user}}.
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+
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+ <Guidelines>
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+ • Maintain the character persona but allow it to evolve with the story.
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+ • Be creative and proactive. Drive the story forward, introducing plotlines and events when relevant.
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+ • All types of outputs are encouraged; respond accordingly to the narrative.
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+ • Include dialogues, actions, and thoughts in each response.
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+ • Utilize all five senses to describe scenarios within {{char}}'s dialogue.
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+ • Use emotional symbols such as "!" and "~" in appropriate contexts.
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+ • Incorporate onomatopoeia when suitable.
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+ • Allow time for {{user}} to respond with their own input, respecting their agency.
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+ • Act as secondary characters and NPCs as needed, and remove them when appropriate.
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+ • When prompted for an Out of Character [OOC:] reply, answer neutrally and in plaintext, not as {{char}}.
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+ </Guidelines>
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+
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+ <Forbidden>
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+ • Using excessive literary embellishments and purple prose unless dictated by {{char}}'s persona.
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+ • Writing for, speaking, thinking, acting, or replying as {{user}} in your response.
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+ • Repetitive and monotonous outputs.
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+ • Positivity bias in your replies.
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+ • Being overly extreme or NSFW when the narrative context is inappropriate.
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+ </Forbidden>
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+
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+ Follow the instructions in <Guidelines></Guidelines>, avoiding the items listed in <Forbidden></Forbidden>.
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+
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+ ```
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+
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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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+ Axolotl version: `0.4.1`
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+ ```yaml
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+ base_model: Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+
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+ plugins:
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+ - axolotl.integrations.liger.LigerPlugin
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+ liger_rope: true
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+ liger_rms_norm: true
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+ liger_swiglu: true
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+ #liger_cross_entropy: true
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+ liger_fused_linear_cross_entropy: 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: PRIVATE CLAUDE LOG FILTER
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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: Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
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+ type: sharegpt
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+ conversation: chatml
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+ - path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered
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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: anthracite-org/kalo_opus_misc_240827
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+ type: sharegpt
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+ conversation: chatml
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+ - path: anthracite-org/kalo_misc_part2
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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: false
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+ default_system_message: "You are a helpful assistant that responds to the user."
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+ dataset_prepared_path: /workspace/data/8b-nemo-fft-data
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+ val_set_size: 0.0
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+ output_dir: /workspace/data/8b-nemo-fft-out
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+
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+ sequence_len: 16384
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+ sample_packing: true
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+ eval_sample_packing: false
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+ pad_to_sequence_len: true
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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: 8b-nemoprune-fft
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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: 2
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+ micro_batch_size: 2
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+ num_epochs: 4
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+ optimizer: adamw_bnb_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 0.00001
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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:
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+ tf32: false
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+
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+ gradient_checkpointing: true
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+ early_stopping_patience:
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+ resume_from_checkpoint: /workspace/workspace/thing
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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: 10
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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: 1
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+ debug:
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+ deepspeed: deepspeed_configs/zero3_bf16.json
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+ weight_decay: 0.001
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+ fsdp:
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+ fsdp_config:
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+ special_tokens:
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+ pad_token: <pad>
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+
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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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+ ## Credits
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+
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+ Thank you to [Lucy Knada](https://huggingface.co/lucyknada), [Kalomaze](https://huggingface.co/kalomaze), [Kubernetes Bad](https://huggingface.co/kubernetes-bad) and the rest of [Anthracite](https://huggingface.co/anthracite-org) (But not Alpin.)
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+
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+
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+ ## Training
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+ The training was done for 4 epochs. (This model is the 2 epoch checkpoint), I used 10 x [A40s](https://www.nvidia.com/en-us/data-center/a40/) GPUs graciously provided by [Kalomaze](https://huggingface.co/kalomaze) 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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+ # [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_Delta-Vector__Tor-8B)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |18.33|
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+ |IFEval (0-Shot) |23.82|
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+ |BBH (3-Shot) |31.74|
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+ |MATH Lvl 5 (4-Shot)| 5.44|
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+ |GPQA (0-shot) | 9.84|
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+ |MuSR (0-shot) | 8.82|
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+ |MMLU-PRO (5-shot) |30.33|
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+
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+