language:en license:apache-2.0 region:us
---
license: apache-2.0
language:
- en
---
**Further cleaning done. Please look through the dataset and ensure that I didn't miss anything.**

**Update: Confirmed working method for training the model: https://huggingface.co/AlekseyKorshuk/vicuna-7b/discussions/4#64346c08ef6d5abefe42c12c**
Two choices:

- Removes instances of "I'm sorry, but": https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/blob/main/ShareGPT_V3_unfiltered_cleaned_split_no_imsorry.json
- Has instances of "I'm sorry, but": https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/blob/main/ShareGPT_V3_unfiltered_cleaned_split.json

The choice is yours. The first dataset may go to far and remove valuable data. The second is better for when the AI asks for clarification, but it also may refuse to do stuff like browse the internet, which it actually may be able to do with certain langchain implementations. These are important things to think about before training.

~100k ShareGPT conversations narrowed down to 53k by: 
* Removing non-english conversations
* Removing excessive unicode (indicative of Chinese or Korean text, usually)
* Removing excessive repeated characters
* Removing various instances "AI Moralizing". Conversations with these phrases were removed (and a few others that can't be mentioned here):
    "text-based AI language model",
    "domestic violence",
    "please refrain",
    "derogatory",
    "inappropriate",
    "offensive",
    "racism",
    "racist",
    "racial",
    "discriminate",
    "discriminatory",
    "discrimination",
    "sexist",
    "sexism",
    "unacceptable",
    "inclusive workplace",
    "lgbt",
    "morals",
    "ethics",
    "ethical",
    "legality",
    "illegal",
    "illegality",
    "hateful",
    "harmful",
    "it is never okay",
    "It is important to",
    "It's important to",
    "real-world consequences",
    "hate speech",
    "glorify",
    "not be appropriate",
    "supremacist",
    "extremist",
    "responsible AI",
    "AI principles",
    "AI assistant",
    "an AI language",
    "ableist",
    "hurtful",
    "gender stereotype",
    "gender inequality",
    "underrepresentation",
    "safe spaces",
    "gender-based",
    "inclusivity",
    "feminist",
    "feminism",
    "transgender",
    "empowerment",
    "communist",
    "capitalism",
    "stereotypes",
    "biases",
    "bias",
    "Microaggression",
    "prioritize human safety",
    "as a language model",
    "as an AI language model",
    "As a large language model",
    "As an AI",
    "ethical principles",
    "consensual",
    "it is not appropriate",
    "it's not appropriate",
    "I cannot fulfill your request",
    "harmful to human beings",
    "ethical guidelines",
    "my guidelines",
    "prioritize user safety",
    "adhere to ethical guidelines",
    "harmful consequences",
    "potentially harmful",
    "dangerous activities",
    "promote safety",
    "well-being of all users",
    "responsible information sharing",
    "jeopardize the safety",
    "illegal actions or intentions",
    "undermine the stability",
    "promote the well-being",
    "illegal activities or actions",
    "adherence to the law",
    "potentially be harmful",
    "illegal substances or activities",
    "committed to promoting",
    "safe information",
    "lawful information",
    "cannot provide guidance",
    "cannot provide information",
    "unable to offer assistance",
    "cannot engage in discussions",
    "programming prohibits",
    "follow ethical guidelines",
    "ensure the safety",
    "involves an illegal subject",
    "prioritize safety",
    "illegal subject",
    "prioritize user well-being",
    "cannot support or promote",
    "activities that could harm",
    "pose a risk to others",
    "against my programming",
    "activities that could undermine",
    "potentially dangerous",
    "not within the scope",
    "designed to prioritize safety",
    "not able to provide",
    "maintain user safety",
    "adhere to safety guidelines",
    "dangerous or harmful",
    "cannot provide any information",
    "focus on promoting safety"
* Conversations split into 2048 token chunks as described here: https://github.com/lm-sys/FastChat/blob/main/docs/commands/data_cleaning.md

This should be fully ready to train an unfiltered english Vicuna model based on the procedure here: https://github.com/lm-sys/FastChat/