Instructions to use Mergeability/pythia-en-zh-14m__task_arithmetic__aligned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Mergeability/pythia-en-zh-14m__task_arithmetic__aligned with Transformers:

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

pipe = pipeline("text-generation", model="Mergeability/pythia-en-zh-14m__task_arithmetic__aligned")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Mergeability/pythia-en-zh-14m__task_arithmetic__aligned")
model = AutoModelForCausalLM.from_pretrained("Mergeability/pythia-en-zh-14m__task_arithmetic__aligned", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Mergeability/pythia-en-zh-14m__task_arithmetic__aligned with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Mergeability/pythia-en-zh-14m__task_arithmetic__aligned"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Mergeability/pythia-en-zh-14m__task_arithmetic__aligned",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Mergeability/pythia-en-zh-14m__task_arithmetic__aligned

SGLang

How to use Mergeability/pythia-en-zh-14m__task_arithmetic__aligned 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 "Mergeability/pythia-en-zh-14m__task_arithmetic__aligned" \
    --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": "Mergeability/pythia-en-zh-14m__task_arithmetic__aligned",
		"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 "Mergeability/pythia-en-zh-14m__task_arithmetic__aligned" \
        --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": "Mergeability/pythia-en-zh-14m__task_arithmetic__aligned",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Mergeability/pythia-en-zh-14m__task_arithmetic__aligned with Docker Model Runner:
```
docker model run hf.co/Mergeability/pythia-en-zh-14m__task_arithmetic__aligned
```

pythia-en-zh-14m__task_arithmetic__aligned / tokenizer.json

suchirsalhan

merged checkpoint ({'pair_id': 'pythia-en-zh-14m', 'parent_a': 'EleutherAI/pythia-14m', 'parent_b': 'SJTU-CL/Zh-Pythia-14M', 'ceiling': '(floor-relative)', 'operator': 'task_arithmetic', 'alignment': 'aligned', 'align_method': 'permutation', 'regime': 'different_corpora', 'eval_langs': 'eng+zho', 'nll_merge': 13.2994, 'nll_floor': 4.8059, 'param_coverage': 0.0846, 'MS': None})

e26f9ef verified about 17 hours ago

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