Model Stock: All we need is just a few fine-tuned models
Paper • 2403.19522 • Published • 15
How to use mergekit-community/MN-Hekate-Noctiluca-12B with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="mergekit-community/MN-Hekate-Noctiluca-12B")
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages) # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("mergekit-community/MN-Hekate-Noctiluca-12B")
model = AutoModelForCausalLM.from_pretrained("mergekit-community/MN-Hekate-Noctiluca-12B")
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]:]))How to use mergekit-community/MN-Hekate-Noctiluca-12B with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mergekit-community/MN-Hekate-Noctiluca-12B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "mergekit-community/MN-Hekate-Noctiluca-12B",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/mergekit-community/MN-Hekate-Noctiluca-12B
How to use mergekit-community/MN-Hekate-Noctiluca-12B with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "mergekit-community/MN-Hekate-Noctiluca-12B" \
--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": "mergekit-community/MN-Hekate-Noctiluca-12B",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'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 "mergekit-community/MN-Hekate-Noctiluca-12B" \
--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": "mergekit-community/MN-Hekate-Noctiluca-12B",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'How to use mergekit-community/MN-Hekate-Noctiluca-12B with Docker Model Runner:
docker model run hf.co/mergekit-community/MN-Hekate-Noctiluca-12B
docker model run hf.co/mergekit-community/MN-Hekate-Noctiluca-12BThis is a merge of pre-trained language models created using mergekit.
This model was merged using the Model Stock merge method using mergekit-community/MN-Hekate-Pyrtania-12B as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
out_dtype: bfloat16
merge_method: model_stock
base_model: mergekit-community/MN-Hekate-Pyrtania-12B
slices:
- sources:
- model: mergekit-community/MN-Hekate-Pyrtania-12B
layer_range: [0, 12]
parameters:
weight: 3
- model: yamatazen/BlueLight-12B
layer_range: [0, 12]
- model: PocketDoc/Dans-SakuraKaze-V1.0.0-12b
layer_range: [0, 12]
- sources:
- model: mergekit-community/MN-Hekate-Pyrtania-12B
layer_range: [12, 16]
- model: LatitudeGames/Wayfarer-12B
layer_range: [12, 16]
- model: PocketDoc/Dans-SakuraKaze-V1.0.0-12b
layer_range: [12, 16]
- model: yamatazen/BlueLight-12B
layer_range: [12, 16]
- model: yamatazen/LoyalMaid-12B
layer_range: [12, 16]
- model: mergekit-community/MN-Hekate-Episkopos-17B
layer_range: [12, 16]
- model: mergekit-community/MN-Hekate-Limenoskopos-17B
layer_range: [12, 16]
- sources:
- model: mergekit-community/MN-Hekate-Pyrtania-12B
layer_range: [16, 20]
- model: LatitudeGames/Wayfarer-12B
layer_range: [16, 20]
- model: PocketDoc/Dans-SakuraKaze-V1.0.0-12b
layer_range: [16, 20]
- model: yamatazen/BlueLight-12B
layer_range: [16, 20]
- model: yamatazen/LoyalMaid-12B
layer_range: [16, 20]
- model: mergekit-community/MN-Hekate-Episkopos-17B
layer_range: [16, 20]
- model: mergekit-community/MN-Hekate-Episkopos-17B
layer_range: [20, 24]
- model: mergekit-community/MN-Hekate-Limenoskopos-17B
layer_range: [16, 20]
- model: mergekit-community/MN-Hekate-Limenoskopos-17B
layer_range: [20, 24]
- sources:
- model: mergekit-community/MN-Hekate-Pyrtania-12B
layer_range: [20, 28]
- model: LatitudeGames/Wayfarer-12B
layer_range: [20, 28]
- model: nbeerbower/mistral-nemo-gutenberg-12B-v4
layer_range: [20, 28]
- model: PocketDoc/Dans-SakuraKaze-V1.0.0-12b
layer_range: [20, 28]
- model: yamatazen/BlueLight-12B
layer_range: [20, 28]
- model: yamatazen/LoyalMaid-12B
layer_range: [20, 28]
- model: mergekit-community/MN-Hekate-Episkopos-17B
layer_range: [24, 32]
- model: mergekit-community/MN-Hekate-Episkopos-17B
layer_range: [36, 44]
- model: mergekit-community/MN-Hekate-Limenoskopos-17B
layer_range: [24, 32]
- model: mergekit-community/MN-Hekate-Limenoskopos-17B
layer_range: [36, 44]
- sources:
- model: mergekit-community/MN-Hekate-Pyrtania-12B
layer_range: [28, 32]
- model: LatitudeGames/Wayfarer-12B
layer_range: [28, 32]
- model: nbeerbower/mistral-nemo-bophades-12B
layer_range: [28, 32]
- model: nbeerbower/mistral-nemo-gutenberg-12B-v4
layer_range: [28, 32]
- model: PocketDoc/Dans-SakuraKaze-V1.0.0-12b
layer_range: [28, 32]
- model: yamatazen/BlueLight-12B
layer_range: [28, 32]
- model: yamatazen/LoyalMaid-12B
layer_range: [28, 32]
- model: mergekit-community/MN-Hekate-Episkopos-17B
layer_range: [32, 36]
- model: mergekit-community/MN-Hekate-Episkopos-17B
layer_range: [44, 48]
- model: mergekit-community/MN-Hekate-Limenoskopos-17B
layer_range: [32, 36]
- model: mergekit-community/MN-Hekate-Limenoskopos-17B
layer_range: [44, 48]
- sources:
- model: mergekit-community/MN-Hekate-Pyrtania-12B
layer_range: [32, 40]
parameters:
weight: 2
- model: nbeerbower/mistral-nemo-bophades-12B
layer_range: [32, 40]
- model: nbeerbower/mistral-nemo-gutenberg-12B-v4
layer_range: [32, 40]
- model: yamatazen/BlueLight-12B
layer_range: [32, 40]
- model: yamatazen/LoyalMaid-12B
layer_range: [32, 40]
- model: mergekit-community/MN-Hekate-Episkopos-17B
layer_range: [48, 56]
- model: mergekit-community/MN-Hekate-Limenoskopos-17B
layer_range: [48, 56]
parameters:
weight: 2
Install from pip and serve model
# Install vLLM from pip: pip install vllm# Start the vLLM server: vllm serve "mergekit-community/MN-Hekate-Noctiluca-12B"# Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mergekit-community/MN-Hekate-Noctiluca-12B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'