Instructions to use SlayerLab/pollock-mini-lm-125m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SlayerLab/pollock-mini-lm-125m with Transformers:

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

pipe = pipeline("text-generation", model="SlayerLab/pollock-mini-lm-125m")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("SlayerLab/pollock-mini-lm-125m")
model = AutoModelForCausalLM.from_pretrained("SlayerLab/pollock-mini-lm-125m", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use SlayerLab/pollock-mini-lm-125m with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SlayerLab/pollock-mini-lm-125m"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SlayerLab/pollock-mini-lm-125m",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/SlayerLab/pollock-mini-lm-125m

SGLang

How to use SlayerLab/pollock-mini-lm-125m 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 "SlayerLab/pollock-mini-lm-125m" \
    --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": "SlayerLab/pollock-mini-lm-125m",
		"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 "SlayerLab/pollock-mini-lm-125m" \
        --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": "SlayerLab/pollock-mini-lm-125m",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use SlayerLab/pollock-mini-lm-125m with Docker Model Runner:
```
docker model run hf.co/SlayerLab/pollock-mini-lm-125m
```

pollock-mini-lm-125m / LICENSE.md

dawidmajewski

Release Pollock 1.4 (r006)

a2e53d9 verified 6 days ago

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Informacja licencyjna / Licensing notice

Kod / Code

Implementacja treningowa projektu bazuje na karpathy/nanoGPT, udostępnianym na licencji MIT:

https://github.com/karpathy/nanoGPT/blob/master/LICENSE

Elementy kodu rozpowszechniane razem z projektem pozostają objęte właściwymi informacjami licencyjnymi ich autorów. Licencja MIT dotycząca nanoGPT nie staje się automatycznie licencją danych treningowych ani wag modelu.

The training implementation is based on karpathy/nanoGPT, which is distributed under the MIT License:

https://github.com/karpathy/nanoGPT/blob/master/LICENSE

Code components distributed with the project remain subject to their respective authors' license notices. The nanoGPT MIT License does not automatically become the license of the training data or model weights.

Korpus i wagi / Corpus and weights

Model został wytrenowany na SlayerLab/minimal-en-corpus-2.5b, agregacie danych z wielu źródeł. Korpus nie nadaje dokumentom jednej wspólnej licencji; każdy dokument zachowuje identyfikator źródła i podlega warunkom, licencjom oraz ograniczeniom właściwego upstreamowego datasetu.

Ze względu na mieszany charakter tych warunków repozytorium modelu używa metadanej Hugging Face license: other. Nie jest to przyznanie dodatkowych praw do materiałów źródłowych. Użytkownik powinien przed użyciem, redystrybucją lub zastosowaniem komercyjnym zapoznać się z kartą korpusu i warunkami wszystkich właściwych źródeł:

https://huggingface.co/datasets/SlayerLab/minimal-en-corpus-2.5b

The model was trained on SlayerLab/minimal-en-corpus-2.5b, an aggregate of multiple data sources. The corpus does not apply a single common license to its documents; each document retains its source identifier and remains subject to the terms, licenses, and restrictions of the applicable upstream dataset.

Because these terms are mixed, the model repository uses the Hugging Face metadata value license: other. This notice does not grant additional rights to upstream materials. Before use, redistribution, or commercial application, users should review the corpus card and the terms of every applicable source:

https://huggingface.co/datasets/SlayerLab/minimal-en-corpus-2.5b