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))