Instructions to use S4nfs/Neeto-1.0-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use S4nfs/Neeto-1.0-8b with Transformers:

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

pipe = pipeline("text-generation", model="S4nfs/Neeto-1.0-8b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("S4nfs/Neeto-1.0-8b")
model = AutoModelForCausalLM.from_pretrained("S4nfs/Neeto-1.0-8b", 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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use S4nfs/Neeto-1.0-8b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "S4nfs/Neeto-1.0-8b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "S4nfs/Neeto-1.0-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/S4nfs/Neeto-1.0-8b

SGLang

How to use S4nfs/Neeto-1.0-8b 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 "S4nfs/Neeto-1.0-8b" \
    --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": "S4nfs/Neeto-1.0-8b",
		"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 "S4nfs/Neeto-1.0-8b" \
        --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": "S4nfs/Neeto-1.0-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use S4nfs/Neeto-1.0-8b with Docker Model Runner:
```
docker model run hf.co/S4nfs/Neeto-1.0-8b
```

Nice and Great Work

by deleted - opened Sep 9, 2025

Discussion

deleted

Sep 9, 2025

Hey Sagar Verma, very wonderful and great work, I’m really impressed. Are you interested in collaborating with me? I also build AI models and was curious why you chose LLaMA specifically, since there are other models around 8B that can understand prompts better and give stronger explanations. Personally, I feel LLaMA lacks in understanding. But as of I see that the LLaMA have very less refusal rates and censorship than other models

S4nfs

Owner Sep 11, 2025

•

edited Sep 11, 2025

Thanks @UJJAWAL-TYAGI for noticing the design choice. LLaMA v3 strikes a solid balance between reasoning and deployment efficiency. To uncensor an LLM, I use the abliteration method, leveraging activations from harmless vs. harmful prompts to find a refusal direction, then adjusting weights to stop refusals. This is often crucial for medical use cases. I’m also experimenting with another model with near-zero refusal rates for defense and cyber-security purpose, though it does raise ethical considerations.

Article: https://www.lesswrong.com/posts/jGuXSZgv6qfdhMCuJ/refusal-in-llms-is-mediated-by-a-single-direction

Also I’m always open to collaborating, feel free to ping me on LinkedIn or X anytime.

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