Instructions to use Mook21/gpt2-medium-football-commentary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mook21/gpt2-medium-football-commentary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Mook21/gpt2-medium-football-commentary")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Mook21/gpt2-medium-football-commentary") model = AutoModelForMultimodalLM.from_pretrained("Mook21/gpt2-medium-football-commentary") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Mook21/gpt2-medium-football-commentary with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Mook21/gpt2-medium-football-commentary" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Mook21/gpt2-medium-football-commentary", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Mook21/gpt2-medium-football-commentary
- SGLang
How to use Mook21/gpt2-medium-football-commentary 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 "Mook21/gpt2-medium-football-commentary" \ --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": "Mook21/gpt2-medium-football-commentary", "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 "Mook21/gpt2-medium-football-commentary" \ --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": "Mook21/gpt2-medium-football-commentary", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Mook21/gpt2-medium-football-commentary with Docker Model Runner:
docker model run hf.co/Mook21/gpt2-medium-football-commentary
GPT-2 Medium — генерация футбольных комментариев
Дообученная GPT-2 Medium (355M) на корпусе текстовых комментариев футбольных матчей. Модель продолжает любой промпт в стиле реальной ленты событий: «Attempt missed…», «Foul by…», «Goal! …», «Substitution…».
Код, ноутбук и отчёт: https://github.com/ovelsad/gpt2-medium-football-commentary
Использование
from transformers import GPT2LMHeadModel, GPT2Tokenizer
repo = "Mook21/gpt2-medium-football-commentary"
tok = GPT2Tokenizer.from_pretrained(repo)
model = GPT2LMHeadModel.from_pretrained(repo)
inputs = tok("In the 90th minute", return_tensors="pt")
out = model.generate(**inputs, max_new_tokens=80, do_sample=True,
temperature=0.9, top_p=0.95, top_k=50,
pad_token_id=tok.eos_token_id)
print(tok.decode(out[0], skip_special_tokens=True))
Метрики (валидация)
| Метрика | Базовая GPT-2 Medium | Эта модель |
|---|---|---|
| Perplexity ↓ | 6.41 | 1.57 |
| BLEU ↑ | 0.0187 | 0.6323 |
| MOS (1..5) ↑ | 2.91 | 4.48 |
Данные и обучение
- Данные: Football Events — 941 009 событий из 9074 матчей топ-5 европейских лиг (2011–2017).
- Корпус собран по матчам (заголовок + хронология событий +
<|endoftext|>), токенизирован в поток и нарезан на блоки по 256. - Обучение: Causal LM, 3 эпохи, batch 8 × grad_accum 4, lr 5e-5, fp16, GPU Tesla T4.
Ограничения
- Модель генерирует события внутри матча, но не моделирует структуру матча целиком.
- В именах с диакритикой возможны единичные артефакты кодировки исходных данных (приведены к латинской транслитерации).
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Model tree for Mook21/gpt2-medium-football-commentary
Base model
openai-community/gpt2-medium