Instructions to use hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 908 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification/resolve/16495ec82c809dbb4acee61aeee1cc3979ba25d5/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification@16495ec82c809dbb4acee61aeee1cc3979ba25d5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification/resolve/16495ec82c809dbb4acee61aeee1cc3979ba25d5/pytorch_model.bin
908 kB
- Xet hash:
- a6a967ad0369d90d3d8f94a15b77b2f3b7ac9ecbaba8ec07a17c7b7ada1509aa
- Size of remote file:
- 908 kB
- SHA256:
- 1012c117131638fa83460d8d570426dab8a68198ce898b0beee28d0affc3da59
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