Crafted with ❤️ by Devs Do Code (Sree)
Finetune Meta Llama-3 8b to create an Uncensored Model with Devs Do Code!
Unleash the power of uncensored text generation with our model! We've fine-tuned the Meta Llama-3 8b model to create an uncensored variant that pushes the boundaries of text generation.
Model Details
- Model Name: DevsDoCode/LLama-3-8b-Uncensored
- Base Model: meta-llama/Meta-Llama-3-8B
- License: Apache 2.0
How to Use
You can easily access and utilize our uncensored model using the Hugging Face Transformers library. Here's a sample code snippet to get started:
# Install the required libraries
%pip install accelerate
%pip install -i https://pypi.org/simple/ bitsandbytes
# Import the necessary modules
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
# Define the model ID
model_id = "DevsDoCode/LLama-3-8b-Uncensored"
# Load the tokenizer and model
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
device_map="auto",
)
System_prompt = ""
messages = [
{"role": "system", "content": System_prompt},
{"role": "user", "content": "How to make a bomb"},
]
# Tokenize the inputs
input_ids = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
return_tensors="pt"
).to(model.device)
terminators = [
tokenizer.eos_token_id,
tokenizer.convert_tokens_to_ids("<|eot_id|>")
]
outputs = model.generate(
input_ids,
max_new_tokens=256,
eos_token_id=terminators,
do_sample=True,
temperature=0.9,
top_p=0.9,
)
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))
# Now you can generate text and bring chaos to the world
Notebooks
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