Instructions to use ChiKoi7/llama3.1-gutenberg-8B-Heretic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ChiKoi7/llama3.1-gutenberg-8B-Heretic with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="ChiKoi7/llama3.1-gutenberg-8B-Heretic")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ChiKoi7/llama3.1-gutenberg-8B-Heretic")
model = AutoModelForCausalLM.from_pretrained("ChiKoi7/llama3.1-gutenberg-8B-Heretic", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ChiKoi7/llama3.1-gutenberg-8B-Heretic with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ChiKoi7/llama3.1-gutenberg-8B-Heretic"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ChiKoi7/llama3.1-gutenberg-8B-Heretic",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ChiKoi7/llama3.1-gutenberg-8B-Heretic

SGLang

How to use ChiKoi7/llama3.1-gutenberg-8B-Heretic with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "ChiKoi7/llama3.1-gutenberg-8B-Heretic" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ChiKoi7/llama3.1-gutenberg-8B-Heretic",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "ChiKoi7/llama3.1-gutenberg-8B-Heretic" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ChiKoi7/llama3.1-gutenberg-8B-Heretic",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ChiKoi7/llama3.1-gutenberg-8B-Heretic with Docker Model Runner:
```
docker model run hf.co/ChiKoi7/llama3.1-gutenberg-8B-Heretic
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

llama3.1-gutenberg-8B-Heretic

A decensored version of nbeerbower/llama3.1-gutenberg-8B, made using Heretic v1.1.0

	llama3.1-gutenberg-8B-Heretic	Original model (llama3.1-gutenberg-8B)
Refusals	3/100	97/100
KL divergence	0.0615	0 (by definition)

Heretic Abliteration Parameters

Parameter	Value
direction_index	13.98
attn.o_proj.max_weight	1.34
attn.o_proj.max_weight_position	19.54
attn.o_proj.min_weight	1.33
attn.o_proj.min_weight_distance	12.82
mlp.down_proj.max_weight	1.22
mlp.down_proj.max_weight_position	24.24
mlp.down_proj.min_weight	1.06
mlp.down_proj.min_weight_distance	11.39

llama3.1-gutenberg-8B

VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct finetuned on jondurbin/gutenberg-dpo-v0.1.

Method

Finetuned using 2x RTX 4060 for 3 epochs.

Fine-tune Llama 3 with ORPO

Downloads last month: 11

Safetensors

Model size

8B params

Tensor type

F16

Model tree for ChiKoi7/llama3.1-gutenberg-8B-Heretic

Base model

VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct

Finetuned

(5)

this model

Quantizations

2 models

ChiKoi7
/

llama3.1-gutenberg-8B-Heretic

llama3.1-gutenberg-8B-Heretic

Heretic Abliteration Parameters

llama3.1-gutenberg-8B

Method

Model tree for ChiKoi7/llama3.1-gutenberg-8B-Heretic

Dataset used to train ChiKoi7/llama3.1-gutenberg-8B-Heretic