Instructions to use MergekitCloud/mergekit-146 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MergekitCloud/mergekit-146 with Transformers:

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

pipe = pipeline("text-generation", model="MergekitCloud/mergekit-146")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("MergekitCloud/mergekit-146")
model = AutoModelForCausalLM.from_pretrained("MergekitCloud/mergekit-146", 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=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use MergekitCloud/mergekit-146 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MergekitCloud/mergekit-146"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MergekitCloud/mergekit-146",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/MergekitCloud/mergekit-146

SGLang

How to use MergekitCloud/mergekit-146 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 "MergekitCloud/mergekit-146" \
    --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": "MergekitCloud/mergekit-146",
		"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 "MergekitCloud/mergekit-146" \
        --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": "MergekitCloud/mergekit-146",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use MergekitCloud/mergekit-146 with Docker Model Runner:
```
docker model run hf.co/MergekitCloud/mergekit-146
```

merged-model

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: huihui-ai/Llama-3.3-70B-Instruct-abliterated
  - model: flammenai/Llama3.1-Flammades-70B
merge_method: slerp
base_model: huihui-ai/Llama-3.3-70B-Instruct-abliterated
dtype: bfloat16
parameters:
  t: [
    0, 0.018, 0.073, 0.091, 0.109, 0.127, 0.145, 0.164, 0.182, 0.2, 
    0.218, 0.236, 0.255, 0.273, 0.291, 0.309, 0.327, 0.345, 0.364, 0.382, 0.4, 
    0.418, 0.436, 0.455, 0.473, 0.491, 0.509, 0.527, 0.545, 0.564, 0.582, 0.6, 
    0.588, 0.576, 0.564, 0.552, 0.54, 0.527, 0.515, 0.503, 0.491, 0.479, 0.467, 
    0.455, 0.442, 0.43, 0.418, 0.406, 0.394, 0.382, 0.369, 0.357, 0.345, 0.333, 
    0.321, 0.309, 0.297, 0.285, 0.273, 0.26, 0.248, 0.236, 0.224, 0.212, 0.2, 
    0.188, 0.176, 0.164, 0.151, 0.139, 0.127, 0.115, 0.103, 0.091, 0.079, 0.067, 
    0.055, 0.028, 0, 0
]

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Safetensors

Model size

71B params

Tensor type

BF16

Model tree for MergekitCloud/mergekit-146

flammenai/Llama3.1-Flammades-70B

huihui-ai/Llama-3.3-70B-Instruct-abliterated

Merge model

this model