Instructions to use netcat420/MFANNv0.22.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use netcat420/MFANNv0.22.1 with Transformers:

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

pipe = pipeline("text-generation", model="netcat420/MFANNv0.22.1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("netcat420/MFANNv0.22.1")
model = AutoModelForCausalLM.from_pretrained("netcat420/MFANNv0.22.1", 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 netcat420/MFANNv0.22.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "netcat420/MFANNv0.22.1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "netcat420/MFANNv0.22.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/netcat420/MFANNv0.22.1

SGLang

How to use netcat420/MFANNv0.22.1 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 "netcat420/MFANNv0.22.1" \
    --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": "netcat420/MFANNv0.22.1",
		"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 "netcat420/MFANNv0.22.1" \
        --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": "netcat420/MFANNv0.22.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use netcat420/MFANNv0.22.1 with Docker Model Runner:
```
docker model run hf.co/netcat420/MFANNv0.22.1
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

this is the bugfix release to MFANNv0.22 which had errors involving refusing to generate a response to certain questions, usually by asking you what you would like to do and ignoring your question, along with some perplexity issues. i suspect this has to do with the DARE-TIES merging i have been doing, which up until now has actually proven to work well but i guess after a good bit of iterations pass, degradation appears to show up. so for the time being im sticking to this new SLERP merging routine i have planned.

designed to be a generally intelligent chain of thought reasoner model. this model is currently still in pre release v0.x beta, and may produce responses not suitable for all audiences due to its uncensored nature.

Thank you so much to @mlabonne for creating the base model mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated for this experiment! please go show him some love too!

System prompt:

Downloads last month: 10

Safetensors

Model size

8B params

Tensor type

F32

Model tree for netcat420/MFANNv0.22.1

Base model

netcat420/MFANN-llama3.1-abliterated-v2

Finetuned

(1)

this model

Merges

1 model

Quantizations

6 models

netcat420
/

MFANNv0.22.1

Model tree for netcat420/MFANNv0.22.1

Dataset used to train netcat420/MFANNv0.22.1