Instructions to use smiled0g/preflop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smiled0g/preflop with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="smiled0g/preflop")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("smiled0g/preflop") model = AutoModelForSequenceClassification.from_pretrained("smiled0g/preflop", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from smiled0g/preflop: direct link, hf CLI and curl.
- Browser
- Download file 2.15 GB
-
https://huggingface.co/smiled0g/preflop/resolve/main/optimizer.pt
- Command line
-
hf download hf://smiled0g/preflop/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/smiled0g/preflop/resolve/main/optimizer.pt
2.15 GB
- Xet hash:
- c37ca9f821953479c471b1cdd5e7211d7860cbf5815e94f03efd329550fee0be
- Size of remote file:
- 2.15 GB
- SHA256:
- 1929395525d23ba461b252f479e75a2ab66c1d1ebc773f71d3e64095208c5035
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