Instructions to use NeuR0mancR/Neural-v1-24B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NeuR0mancR/Neural-v1-24B with Transformers:

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

pipe = pipeline("text-generation", model="NeuR0mancR/Neural-v1-24B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("NeuR0mancR/Neural-v1-24B")
model = AutoModelForCausalLM.from_pretrained("NeuR0mancR/Neural-v1-24B", 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 NeuR0mancR/Neural-v1-24B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NeuR0mancR/Neural-v1-24B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NeuR0mancR/Neural-v1-24B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/NeuR0mancR/Neural-v1-24B

SGLang

How to use NeuR0mancR/Neural-v1-24B 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 "NeuR0mancR/Neural-v1-24B" \
    --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": "NeuR0mancR/Neural-v1-24B",
		"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 "NeuR0mancR/Neural-v1-24B" \
        --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": "NeuR0mancR/Neural-v1-24B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use NeuR0mancR/Neural-v1-24B with Docker Model Runner:
```
docker model run hf.co/NeuR0mancR/Neural-v1-24B
```

NeuR0mancR commited on May 6

Commit

8ac26bd

verified ·

1 Parent(s): 455afb2

Update mergekit_config.yml

Browse files

Files changed (1) hide show

mergekit_config.yml +60 -13

mergekit_config.yml CHANGED Viewed

@@ -1,13 +1,60 @@
-base_model: D:\Lab\models\inter\aligned_stock
-dtype: bfloat16
-merge_method: slerp
-modules:
-  default:
-    slices:
-    - sources:
-      - layer_range: [0, 40]
-        model: D:\Lab\models\inter\aligned_stock
-      - layer_range: [0, 40]
-        model: D:\Lab\models\inter\aligned_dare
-parameters:
-  t: 0.35

+name: stock
+base_model: TheDrummer/Cydonia-24B-v4.3
+merge_method: model_stock
+dtype: bfloat16
+models:
+  - model: TheDrummer/Cydonia-24B-v4.3
+  - model: zerofata/MS3.2-PaintedFantasy-v2-24B
+  - model: aixonlab/Eurydice-24b-v3.5
+  - model: PocketDoc/Dans-PersonalityEngine-V1.3.0-24b
+---
+name: aligned_stock
+merge_method: nuslerp
+base_model: anthracite-core/Mistral-Small-3.2-24B-Instruct-2506-Text-Only
+dtype: bfloat16
+models:
+  - model: stock
+    parameters:
+      weight: 0.45
+  - model: PocketDoc/Dans-PersonalityEngine-V1.3.0-24b
+    parameters:
+      weight: 0.18
+---
+name: aligned_dare
+merge_method: dare_ties
+base_model: anthracite-core/Mistral-Small-3.2-24B-Instruct-2506-Text-Only
+dtype: bfloat16
+parameters:
+  normalize: false
+  int8_mask: false
+tokenizer_source: ReadyArt/MS3.2-The-Omega-Directive-24B-Unslop-v2.0
+models:
+  - model: ReadyArt/MS3.2-The-Omega-Directive-24B-Unslop-v2.0
+    parameters:
+      weight: 0.5
+      density: 0.5
+  - model: CrucibleLab/M3.2-24B-Loki-V1.3
+    parameters:
+      weight: 0.5
+      density: 0.5
+  - model: Delta-Vector/MS3.2-Austral-Winton
+    parameters:
+      weight: 0.25
+      density: 0.25
+  - model: zerofata/MS3.2-PaintedFantasy-v2-24B
+    parameters:
+      weight: 0.25
+      density: 0.25
+---
+merge_method: slerp
+base_model: aligned_stock
+slices:
+  - sources:
+      - model: aligned_stock
+        layer_range: [0, 40]
+      - model: aligned_dare
+        layer_range: [0, 40]
+parameters:
+  t: 0.35
+dtype: bfloat16
+embed_slerp: true