|
--- |
|
base_model: google/gemma-2-2b-jpn-it |
|
language: |
|
- multilingual |
|
library_name: transformers |
|
license: gemma |
|
license_link: https://ai.google.dev/gemma/terms |
|
pipeline_tag: text-generation |
|
tags: |
|
- nlp |
|
- code |
|
quantized_by: ymcki |
|
widget: |
|
- messages: |
|
- role: user |
|
content: Can you provide ways to eat combinations of bananas and dragonfruits? |
|
--- |
|
|
|
Original model: https://huggingface.co/google/gemma-2-2b-jpn-it |
|
|
|
## Prompt format |
|
|
|
``` |
|
<start_of_turn>user |
|
{prompt}<end_of_turn> |
|
<start_of_turn>model |
|
<end_of_turn> |
|
<start_of_turn>model |
|
|
|
``` |
|
|
|
Note that this model does not support a System prompt. |
|
|
|
This is abliterated model of [`google/gemma-2-2b-jpn-it](https://huggingface.co/google/gemma-2-2b-jpn-it) using the |
|
[method](https://medium.com/@mlabonne/uncensor-any-llm-with-abliteration-d30148b7d43e) |
|
described by mlabonne. |
|
|
|
Layer 18 of the original model was chosen for abliteration. |
|
I also created another layer 17 abliterated model for comparison. |
|
|
|
It is uploaded here to be evaluated by the LLM Leaderboard to see how brain damaged it |
|
is compared to the original model. |
|
|
|
ORPO fine tuning is currently underway to see if it can regain its sanity. You can play with this model first or wait until I am done with the fine tuning. |
|
|
|
## How to run this model |
|
|
|
```py |
|
from transformers import AutoTokenizer, AutoModelForCausalLM |
|
import transformers |
|
import torch |
|
|
|
model_id = "gemma-2-2b-jpn-it-abliterated-18" |
|
dtype = torch.bfloat16 |
|
|
|
tokenizer = AutoTokenizer.from_pretrained(model_id) |
|
model = AutoModelForCausalLM.from_pretrained( |
|
model_id, |
|
device_map="cuda", |
|
torch_dtype=dtype,) |
|
|
|
chat = [ |
|
{ "role": "user", "content": "Write a hello world program" }, |
|
] |
|
prompt = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True) |
|
``` |
|
|
|
## Downloading using huggingface-cli |
|
|
|
First, make sure you have hugginface-cli installed: |
|
|
|
``` |
|
pip install -U "huggingface_hub[cli]" |
|
``` |
|
|
|
Then, you can target the specific file you want: |
|
|
|
``` |
|
huggingface-cli download ymcki/gemma-2-2b-jpn-it-abliterated-18 --include "*" --local-dir ./ |
|
``` |
|
|
|
## Credits |
|
|
|
Thank you mlabonne for describing his abliteration method. |
|
|