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---
language:
- en
- fr
- es
- ru
- zh
- ja
- fa
- code
license: mit
library_name: transformers
base_model:
- fluently-lm/FluentlyLM-Prinum
tags:
- abliterated
- uncensored
- fluently-lm
- fluently
- prinum
- instruct
- trained
- math
- roleplay
- reasoning
- axolotl
- unsloth
- argilla
- qwen2
datasets:
- fluently-sets/ultraset
- fluently-sets/ultrathink
- fluently-sets/reasoning-1-1k
- fluently-sets/MATH-500-Overall
inference: true
pipeline_tag: text-generation
model-index:
- name: FluentlyLM-Prinum
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 80.9
name: strict accuracy
source:
url: >-
https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fluently-lm/FluentlyLM-Prinum
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 59.48
name: normalized accuracy
source:
url: >-
https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fluently-lm/FluentlyLM-Prinum
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 54
name: exact match
source:
url: >-
https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fluently-lm/FluentlyLM-Prinum
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 18.23
name: acc_norm
source:
url: >-
https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fluently-lm/FluentlyLM-Prinum
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 17.26
name: acc_norm
source:
url: >-
https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fluently-lm/FluentlyLM-Prinum
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 53.42
name: accuracy
source:
url: >-
https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fluently-lm/FluentlyLM-Prinum
name: Open LLM Leaderboard
---
# huihui-ai/FluentlyLM-Prinum-abliterated
This is an uncensored version of [fluently-lm/FluentlyLM-Prinum](https://huggingface.co./fluently-lm/FluentlyLM-Prinum) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it).
This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.
## Use with ollama
You can use [huihui_ai/fluentlylm-prinum-abliterated](https://ollama.com/huihui_ai/fluentlylm-prinum-abliterated) directly
```
ollama run huihui_ai/fluentlylm-prinum-abliterated
```
### Donation
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##### Your donation helps us continue our further development and improvement, a cup of coffee can do it.
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```
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``` |