Instructions to use ChaoticNeutrals/Infinitely-Laydiculous-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChaoticNeutrals/Infinitely-Laydiculous-9B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ChaoticNeutrals/Infinitely-Laydiculous-9B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ChaoticNeutrals/Infinitely-Laydiculous-9B") model = AutoModelForCausalLM.from_pretrained("ChaoticNeutrals/Infinitely-Laydiculous-9B") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ChaoticNeutrals/Infinitely-Laydiculous-9B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ChaoticNeutrals/Infinitely-Laydiculous-9B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ChaoticNeutrals/Infinitely-Laydiculous-9B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ChaoticNeutrals/Infinitely-Laydiculous-9B
- SGLang
How to use ChaoticNeutrals/Infinitely-Laydiculous-9B 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 "ChaoticNeutrals/Infinitely-Laydiculous-9B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ChaoticNeutrals/Infinitely-Laydiculous-9B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "ChaoticNeutrals/Infinitely-Laydiculous-9B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ChaoticNeutrals/Infinitely-Laydiculous-9B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ChaoticNeutrals/Infinitely-Laydiculous-9B with Docker Model Runner:
docker model run hf.co/ChaoticNeutrals/Infinitely-Laydiculous-9B
Soon it will be here.
@Lewdiculous
slices:
- sources:
- model: Endevor/InfinityRP-v1-7B
layer_range: [0, 20]
- model: Endevor/InfinityRP-v1-7B
- sources:
- model: l3utterfly/mistral-7b-v0.1-layla-v4
layer_range: [12, 32]
- model: l3utterfly/mistral-7b-v0.1-layla-v4
merge_method: passthrough
dtype: float16
Thank you mate!
What a glorious model name.
The last 9B passthrough with Eris went well, let's see about this one.
Can you add a waifu for this one later?
Lewd is good but I don't think we can go full NSFW on the art lol
maybe something similar to your 6.3
Choose your fighter. (inb4 you use the other ones for models later lmao.)
(inb4 you use the other ones for models later lmao.)
Nah, I'll keep begging for more.
Can I order just one more batch, chef?
Im doing no more for now.
I'm sorry xD
It's fine, thank you, one of these will do nicely!
No worries lmao, let me know which one you want for the merge.
@Nitral-AI - Model rename request: Infinitely-Laydiculous-9B
- Consistant with name as I imagine it's a bit of a pun (lol) and I prefer to capitalize the parameter size.
Unless it looks too bad for you.
If it's alright you can go ahead and update your repo and readme and I'll update accordingly. Cheers mate and happy cooking!
I should try to sleep at a more normal time.
@Nitral-AI I am the one that gets bothered by one letter but that's my whole life :')
Ty <3
Yes I'm still not sleeping fkk
I'm trying this model and I have to say that I really like it. Goisto does great things with the prompt
Another thing, with LM Studio it gives it to me as 13B
{
"name": "D:\Ferramentas\gguf-quantizations\models",
"arch": "llama",
"quant": "Q4_K_S",
"context_length": 32768,
"embedding_length": 4096,
"num_layers": 40,
"rope": {
"freq_base": 10000,
"dimension_count": 128
},
"head_count": 32,
"head_count_kv": 8,
"parameters": "13B"
}











