Instructions to use OddTheGreat/Core_24B_V.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OddTheGreat/Core_24B_V.1 with Transformers:

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

pipe = pipeline("text-generation", model="OddTheGreat/Core_24B_V.1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("OddTheGreat/Core_24B_V.1")
model = AutoModelForCausalLM.from_pretrained("OddTheGreat/Core_24B_V.1")
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

vLLM

How to use OddTheGreat/Core_24B_V.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OddTheGreat/Core_24B_V.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": "OddTheGreat/Core_24B_V.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/OddTheGreat/Core_24B_V.1

SGLang

How to use OddTheGreat/Core_24B_V.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 "OddTheGreat/Core_24B_V.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": "OddTheGreat/Core_24B_V.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 "OddTheGreat/Core_24B_V.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": "OddTheGreat/Core_24B_V.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use OddTheGreat/Core_24B_V.1 with Docker Model Runner:
```
docker model run hf.co/OddTheGreat/Core_24B_V.1
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Core

This is a merge of pretrained language models

With new Mistral recently released, and being slightly better than it predecessor, i wanted to update Apparatus.

Also, i tested new pantheon, and i like how it mimic human expressions and mannerisms, so idea of new merge was born.

Goal of this merge is transfer Apparatus to new Mistral 3.1, and enhance it dialogue capabilities while preserving it stability and ru performance.

It seems that i succeed. Model is smart enough, instruction-following, decently creative and stable.

tested on 250 answers, narration is really good, dialogues too, swipes make difference.

Russian performance still here, no problems with full ru cards and partly translatd ones.

Qvink Memory seems to break something. With it on, replies becomes much shorter.

Better use prebuilt V7 format in ST, but chatML also work fine. T1.01 XTC 0.1 0.1

Is it better than Apparatus? i cannot tell, so your feedback is apperciated.

P.S this model not include vision, but as soon i figure how to merge it in, i will update it.

Downloads last month: 31

Safetensors

Model size

24B params

Tensor type

F16

Model tree for OddTheGreat/Core_24B_V.1

Gryphe/Pantheon-RP-1.8-24b-Small-3.1

OddTheGreat/Apparatus_24B

mrfakename/mistral-small-3.1-24b-instruct-2503-hf

Merge model

this model

Merges

1 model

Quantizations

4 models

Collection including OddTheGreat/Core_24B_V.1

20-30B merges

Collection

10 items • Updated Mar 2 • 4