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))
- Downloads last month
- 213
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.