Instructions to use Nohobby/L3.3-Prikol-70B-v0.4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Nohobby/L3.3-Prikol-70B-v0.4 with Transformers:

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

pipe = pipeline("text-generation", model="Nohobby/L3.3-Prikol-70B-v0.4")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("Nohobby/L3.3-Prikol-70B-v0.4")
model = AutoModelForMultimodalLM.from_pretrained("Nohobby/L3.3-Prikol-70B-v0.4")
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 Nohobby/L3.3-Prikol-70B-v0.4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Nohobby/L3.3-Prikol-70B-v0.4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Nohobby/L3.3-Prikol-70B-v0.4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Nohobby/L3.3-Prikol-70B-v0.4

SGLang

How to use Nohobby/L3.3-Prikol-70B-v0.4 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 "Nohobby/L3.3-Prikol-70B-v0.4" \
    --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": "Nohobby/L3.3-Prikol-70B-v0.4",
		"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 "Nohobby/L3.3-Prikol-70B-v0.4" \
        --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": "Nohobby/L3.3-Prikol-70B-v0.4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Nohobby/L3.3-Prikol-70B-v0.4 with Docker Model Runner:
```
docker model run hf.co/Nohobby/L3.3-Prikol-70B-v0.4
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Prikol

I don't even know anymore

Overview

I have yet to try it UPD: it sucks, bleh

Sometimes mistakes {{user}} for {{char}} and can't think. Other than that, the behavior is similar to the predecessors.

It sometimes gives some funny replies tho, yay!

If you still want to give it a try, here's the cursed text completion preset for cursed models, which makes them somewhat bearable:

https://files.catbox.moe/qr3s64.json

Or this one:

https://files.catbox.moe/97xryh.json

Prompt format: Llama3

Quants

https://huggingface.co/bartowski/Nohobby_L3.3-Prikol-70B-v0.4-GGUF

Merge Details

Step1

base_model: sophosympatheia/Nova-Tempus-70B-v0.2
merge_method: model_stock
dtype: bfloat16
models:
  - model: nbeerbower/Llama-3.1-Nemotron-lorablated-70B
  - model: sophosympatheia/New-Dawn-Llama-3.1-70B-v1.1
tokenizer:
  source: sophosympatheia/Nova-Tempus-70B-v0.2

Step2

models:
  - model: unsloth/DeepSeek-R1-Distill-Llama-70B
  - model: ArliAI/Llama-3.3-70B-ArliAI-RPMax-v1.4
    parameters:
        select_topk:
          - value: [0.18, 0.3, 0.32, 0.38, 0.32, 0.3]
  - model: Nohobby/AbominationSnowPig
    parameters:
        select_topk:
          - value: [0.1, 0.06, 0.05, 0.05, 0.08]
  - model: SicariusSicariiStuff/Negative_LLAMA_70B
    parameters:
        select_topk: 0.17
  - model: mergekit-community/L3.3-L3.1-NewTempusBlated-70B
    parameters:
        select_topk: 0.55
base_model: mergekit-community/L3.3-L3.1-NewTempusBlated-70B
merge_method: sce
parameters:
  int8_mask: true
  rescale: true
  normalize: true
dtype: float32
out_dtype: bfloat16
tokenizer_source: base

Downloads last month: 3

Safetensors

Model size

71B params

Tensor type

BF16

Model tree for Nohobby/L3.3-Prikol-70B-v0.4

ArliAI/Llama-3.3-70B-ArliAI-RPMax-v1.4

Nohobby/AbominationSnowPig

SicariusSicariiStuff/Negative_LLAMA_70B

deepseek-ai/DeepSeek-R1-Distill-Llama-70B

nbeerbower/Llama-3.1-Nemotron-lorablated-70B

sophosympatheia/New-Dawn-Llama-3.1-70B-v1.1

sophosympatheia/Nova-Tempus-70B-v0.2

Merge model

this model

Quantizations

2 models