---
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](https://huggingface.co/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](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/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](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 %}
```
# [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|
---
[](https://github.com/unslothai/unsloth)