---
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
---


<img src="https://cdn-uploads.huggingface.co/production/uploads/65ad2502043d53781aad2ee4/_fMSiKgc791PxxBfubWna.png" alt="image" width="540" height="540" style="margin-bottom: 30px;">

# 💫 Pulsar_7B
A more compliant, uncensored, RP-oriented version of [MTSAIR/multi_verse_model](https://huggingface.co./MTSAIR/multi_verse_model), fine-tuned on carefully selected datasets. It's smart, soulful, and 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](https://wikia.schneedc.com/bot-creation/trappu/introduction) 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](https://huggingface.co./mradermacher/Pulsar_7B-GGUF).

## Formatting
Pulsar_7B works well with Alpaca, it's not a picky model when it comes to formatting. Mistral should be compatible too. The custom chat template from [MTSAIR/multi_verse_model](https://huggingface.co./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 %}
```
<br>

# [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_rmdhirr__Pulsar_7B)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |74.23|
|AI2 Reasoning Challenge (25-Shot)|69.71|
|HellaSwag (10-Shot)              |86.99|
|MMLU (5-Shot)                    |63.72|
|TruthfulQA (0-shot)              |69.28|
|Winogrande (5-shot)              |84.06|
|GSM8k (5-shot)                   |71.65|

---
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.

[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)