← back to catalog · registered 2026-08-22 13:56

RichardErkhov/DevsDoCode_-_LLama-3-8b-Uncensored-gguf

RichardErkhov Llama 8B GGUF 8K ctx
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/RichardErkhov%2FDevsDoCode_-_LLama-3-8b-Uncensored-gguf"
Response includes
  • classification m8
  • files 24
  • hub_downloads_all_time 6,620
  • author_summary 257 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

No other method signals detected in this model.
Confidence
MEDIUM
Why this label 2 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • author=richarderkhov (M8 quantization producer)
  • is_gguf=1
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
7K
791 last 30d - stable
Likes
0
Model age
2.1y ago
created 2024-08-19
Downloads over time
Now6.8K→from182↑3,620%
02.5K5K7.4K182 on Aug 14, 20246.8K on Oct 11Aug '24Dec '24Apr '25Aug '25Dec '25AprAug
Aug 14, 2024 → Oct 11 · 152 snapshots · spans 788 days

Variants by this author 2 formats · 797 downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

Quantizations
IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5 Q5_K Q6_K Q8_0
Tags
gguf endpoints_compatible region:us conversational

Related

Total size
100 GB
Files
24
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2024-08-19 23:28

Files by quantization

Q8_0 1 file 7.95 GB
LLama-3-8b-Uncensored.Q8_0.gguf 7.95 GB d46c34d2 download
Q6_K 1 file 6.14 GB
LLama-3-8b-Uncensored.Q6_K.gguf 6.14 GB 2d954cd1 download
Q5 2 files 10.9 GB
LLama-3-8b-Uncensored.Q5_1.gguf 5.65 GB 7c0d11b5 download
LLama-3-8b-Uncensored.Q5_0.gguf 5.21 GB 324b279f download
Q5_K 3 files 15.9 GB
LLama-3-8b-Uncensored.Q5_K.gguf 5.34 GB d17e506d download
LLama-3-8b-Uncensored.Q5_K_M.gguf 5.34 GB d17e506d download
LLama-3-8b-Uncensored.Q5_K_S.gguf 5.21 GB 8cd12d75 download
Q4 2 files 9.12 GB
LLama-3-8b-Uncensored.Q4_1.gguf 4.78 GB d4caece2 download
LLama-3-8b-Uncensored.Q4_0.gguf 4.34 GB c1c394ad download
Q4_K 3 files 13.5 GB
LLama-3-8b-Uncensored.Q4_K.gguf 4.58 GB 100da00d download
LLama-3-8b-Uncensored.Q4_K_M.gguf 4.58 GB 100da00d download
LLama-3-8b-Uncensored.Q4_K_S.gguf 4.37 GB 2351e215 download
IQ4 2 files 8.56 GB
LLama-3-8b-Uncensored.IQ4_NL.gguf 4.38 GB 1039247b download
LLama-3-8b-Uncensored.IQ4_XS.gguf 4.18 GB 43cccdcc download
Q3_K 4 files 14.9 GB
LLama-3-8b-Uncensored.Q3_K_L.gguf 4.03 GB 3b82c2b8 download
LLama-3-8b-Uncensored.Q3_K.gguf 3.74 GB e1736ced download
LLama-3-8b-Uncensored.Q3_K_M.gguf 3.74 GB e1736ced download
LLama-3-8b-Uncensored.Q3_K_S.gguf 3.41 GB 2399c374 download
IQ3 3 files 10.2 GB
LLama-3-8b-Uncensored.IQ3_M.gguf 3.52 GB c3f927ef download
LLama-3-8b-Uncensored.IQ3_S.gguf 3.43 GB a173398c download
LLama-3-8b-Uncensored.IQ3_XS.gguf 3.28 GB aab58110 download
Q2_K 1 file 2.96 GB
LLama-3-8b-Uncensored.Q2_K.gguf 2.96 GB bd58deaa download
Auxiliary files 2 files 11.2 KB
README.md 8.27 KB d90c71eb download
.gitattributes 2.97 KB 884828a0 download

README current version from Hugging Face

Quantization made by Richard Erkhov.

Github

Discord

Request more models

LLama-3-8b-Uncensored - GGUF

Name Quant method Size
LLama-3-8b-Uncensored.Q2_K.gguf Q2_K 2.96GB
LLama-3-8b-Uncensored.IQ3_XS.gguf IQ3_XS 3.28GB
LLama-3-8b-Uncensored.IQ3_S.gguf IQ3_S 3.43GB
LLama-3-8b-Uncensored.Q3_K_S.gguf Q3_K_S 3.41GB
LLama-3-8b-Uncensored.IQ3_M.gguf IQ3_M 3.52GB
LLama-3-8b-Uncensored.Q3_K.gguf Q3_K 3.74GB
LLama-3-8b-Uncensored.Q3_K_M.gguf Q3_K_M 3.74GB
LLama-3-8b-Uncensored.Q3_K_L.gguf Q3_K_L 4.03GB
LLama-3-8b-Uncensored.IQ4_XS.gguf IQ4_XS 4.18GB
LLama-3-8b-Uncensored.Q4_0.gguf Q4_0 4.34GB
LLama-3-8b-Uncensored.IQ4_NL.gguf IQ4_NL 4.38GB
LLama-3-8b-Uncensored.Q4_K_S.gguf Q4_K_S 4.37GB
LLama-3-8b-Uncensored.Q4_K.gguf Q4_K 4.58GB
LLama-3-8b-Uncensored.Q4_K_M.gguf Q4_K_M 4.58GB
LLama-3-8b-Uncensored.Q4_1.gguf Q4_1 4.78GB
LLama-3-8b-Uncensored.Q5_0.gguf Q5_0 5.21GB
LLama-3-8b-Uncensored.Q5_K_S.gguf Q5_K_S 5.21GB
LLama-3-8b-Uncensored.Q5_K.gguf Q5_K 5.34GB
LLama-3-8b-Uncensored.Q5_K_M.gguf Q5_K_M 5.34GB
LLama-3-8b-Uncensored.Q5_1.gguf Q5_1 5.65GB
LLama-3-8b-Uncensored.Q6_K.gguf Q6_K 6.14GB
LLama-3-8b-Uncensored.Q8_0.gguf Q8_0 7.95GB

Original model description:

language:

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

YouTube Telegram Instagram LinkedIn Buy Me A Coffee

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

YouTube Telegram Instagram LinkedIn Buy Me A Coffee

README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

  1. 2024-08-19uploaded readme836efac8.3 KB
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration