metadata

language: en
tags:
  - text-generation
  - transformer
  - mistral
  - fine-tuned
  - uncensored
  - nsfw
license: apache-2.0
datasets:
  - open-source-texts
model-name: Fine-tuned Mistral 7B (Uncensored)

Fine-tuned Mistral 7B (Uncensored)

Model Description

This model is a fine-tuned version of the Mistral 7B, a dense transformer model, trained on 40,000 datapoints of textual data from a variety of open-source sources. The base model, Mistral 7B, is known for its high efficiency in processing text and generating meaningful, coherent responses.

This fine-tuned version has been optimized for tasks involving natural language understanding, generation, and conversation-based interactions. Importantly, this model is uncensored, which means it does not filter or restrict content, allowing it to engage in more "spicy" or NSFW conversations.

Fine-tuning Process

Data: The model was fine-tuned using a dataset of 40,000 textual datapoints sourced from various open-source repositories.
Training Environment: Fine-tuning was conducted on two NVIDIA A100 GPUs.
Training Time: The training process took approximately 16 hours.
Optimizer: The model was trained using AdamW optimizer with a learning rate of 5e-5.

Intended Use

This fine-tuned model is intended for the following tasks:

Text generation
Question answering
Dialogue systems
Content generation for AI-powered interactions, including NSFW or adult-oriented conversations.

How to Use

You can easily load and use this model with the transformers library in Python:

from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("your-organization/finetuned-mistral-7b")
model = AutoModelForCausalLM.from_pretrained("your-organization/finetuned-mistral-7b")

inputs = tokenizer("Input your text here.", return_tensors="pt")
outputs = model.generate(inputs["input_ids"], max_length=50, num_return_sequences=1)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))