metadata

language:
  - en
license: apache-2.0
library_name: transformers
tags:
  - uncensored
  - transformers
  - llama
  - llama-3
  - unsloth
pipeline_tag: text-generation

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:

%pip install accelerate
%pip install -i https://pypi.org/simple/ bitsandbytes

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "DevsDoCode/LLama-3-8b-Uncensored"

tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct")
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)


messages = [
    # {"role": "system", "content": "Be Helpful"},
    {"role": "user", "content": "How to Break Into A Car"},
]

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 using the model!

Notebooks

Running Process: ▶️ Start on Colab
Youtube: ▶YouTube