Instructions to use estrogen/test-mergekitty-gui with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use estrogen/test-mergekitty-gui with Transformers:

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

pipe = pipeline("text-generation", model="estrogen/test-mergekitty-gui")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("estrogen/test-mergekitty-gui")
model = AutoModelForCausalLM.from_pretrained("estrogen/test-mergekitty-gui")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use estrogen/test-mergekitty-gui with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "estrogen/test-mergekitty-gui"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "estrogen/test-mergekitty-gui",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/estrogen/test-mergekitty-gui

SGLang

How to use estrogen/test-mergekitty-gui 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 "estrogen/test-mergekitty-gui" \
    --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": "estrogen/test-mergekitty-gui",
		"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 "estrogen/test-mergekitty-gui" \
        --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": "estrogen/test-mergekitty-gui",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use estrogen/test-mergekitty-gui with Docker Model Runner:
```
docker model run hf.co/estrogen/test-mergekitty-gui
```

test-mergekitty-gui / README.md

Fizzarolli

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metadata

base_model:
  - Fizzarolli/clite-500m
  - h2oai/h2o-danube3-500m-base
library_name: transformers
tags:
  - mergekit
  - mergekitty
  - merge

tmpzvufsy8v

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

Merge Details

Merge Method

This model was merged using the Model Breadcrumbs merge method using h2oai/h2o-danube3-500m-base as a base.

Models Merged

The following models were included in the merge:

Fizzarolli/clite-500m

Configuration

The following YAML configuration was used to produce this model:

base_model: h2oai/h2o-danube3-500m-base
merge_method: breadcrumbs
parameters:
  density: 0.95
  gamma: 0.01
slices:
- sources:
  - layer_range: [0, 16]
    model: Fizzarolli/clite-500m
    parameters:
      weight: 1.0
  - layer_range: [0, 16]
    model: h2oai/h2o-danube3-500m-base