language:

• en license: apache-2.0 library_name: transformers tags:
• text-generation-inference
• transformers
• unsloth
• mistral
• trl
• dpo
• uncensored
• roleplay
• fine-tune base_model: MTSAIR/multi_verse_model datasets:
• grimulkan/theory-of-mind
• grimulkan/physical-reasoning
• ResplendentAI/Luna_Alpaca
• unalignment/toxic-dpo-v0.2
• kira/math-dpo
• athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW-v1-SHUFFLED model-index:
• name: Pulsar_7B 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: 69.71 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rmdhirr/Pulsar_7B 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: 86.99 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rmdhirr/Pulsar_7B 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: 63.72 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rmdhirr/Pulsar_7B 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: 69.28 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rmdhirr/Pulsar_7B 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: 84.06 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rmdhirr/Pulsar_7B 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: 71.65 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rmdhirr/Pulsar_7B name: Open LLM Leaderboard

💫 Pulsar_7B

⚠️ This is an experimental model!

A more compliant, RP-oriented version of MTSAIR/multi_verse_model, fine-tuned on carefully selected datasets. It's smart, adept at following the desired markdown format and adhering to the provided character card. The first message of the character card significantly influences its writing style. Pulsar_7B pairs well with guidance from CFG Scale and works effectively with PLists + Ali:Chat character cards. Pulsar_7B was fine-tuned on the following datasets:

• grimulkan/theory-of-mind
• grimulkan/physical-reasoning
• ResplendentAI/Luna_Alpaca
• unalignment/toxic-dpo-v0.2
• kira/math-dpo
• athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW-v1-SHUFFLED

Quantizations

Thanks to mradermacher, static GGUF quants are available here.

Formatting/Preset

Pulsar_7B works well with Alpaca, it's not a picky model when it comes to formatting/preset. Mistral should be compatible too. The custom chat template from MTSAIR/multi_verse_model also performs well:

{% for message in messages %}{% if message['role'] == 'user' %}{{ '### Instruction:\n' + message['content'] + '\n### Response:\n' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% elif message['role'] == 'system' %}{{ '### System:\n' + message['content'] + '\n' }}{% endif %}{% endfor %}

Open LLM Leaderboard Evaluation Results

Detailed results can be found here