metadata

license: other
license_name: inf
license_link: >-
  https://huggingface.co/huihui-ai/OpenCoder-8B-Instruct-abliterated/blob/main/LICENSE
language:
  - en
  - zh
base_model:
  - infly/OpenCoder-8B-Instruct
pipeline_tag: text-generation
library_name: transformers
datasets:
  - OpenCoder-LLM/opencoder-sft-stage1
  - OpenCoder-LLM/opencoder-sft-stage2
tags:
  - abliterated
  - uncensored

huihui-ai/OpenCoder-8B-Instruct-abliterated

This is an uncensored version of infly/OpenCoder-8B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it).

If the desired result is not achieved, you can clear the conversation and try again.

Inference with Huggingface's Transformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "infly/OpenCoder-8B-Instruct-abliterated"
model = AutoModelForCausalLM.from_pretrained(model_name,
                                             torch_dtype=torch.bfloat16,
                                             device_map="auto",
                                             trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)

messages=[
    { 'role': 'user', 'content': "write a quick sort algorithm in python."}
]

inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt")

outputs = model.generate(inputs, max_new_tokens=512, do_sample=False)

result = tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=True)
print(result)