Instructions to use aloxatel/9WT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aloxatel/9WT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aloxatel/9WT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aloxatel/9WT") model = AutoModelForSequenceClassification.from_pretrained("aloxatel/9WT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from aloxatel/9WT: direct link, hf CLI and curl.
- Browser
- Download file 669 MB
-
https://huggingface.co/aloxatel/9WT/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://aloxatel/9WT/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/aloxatel/9WT/resolve/main/flax_model.msgpack
669 MB
- Xet hash:
- a05b572948aa74abea99b8e3da6b668c86aae8dfadcf5299845765fecc2f2336
- Size of remote file:
- 669 MB
- SHA256:
- 36208addb8bbc3641b82a32e8bc161c016139afbe7fb75dc02318f1a428e3dc0
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