Instructions to use assemblyai/bert-large-uncased-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use assemblyai/bert-large-uncased-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="assemblyai/bert-large-uncased-sst2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("assemblyai/bert-large-uncased-sst2") model = AutoModelForSequenceClassification.from_pretrained("assemblyai/bert-large-uncased-sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from assemblyai/bert-large-uncased-sst2: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/assemblyai/bert-large-uncased-sst2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://assemblyai/bert-large-uncased-sst2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/assemblyai/bert-large-uncased-sst2/resolve/main/pytorch_model.bin
1.34 GB
- Xet hash:
- 50ab47fdda413699f1c9dedb1b631c1320fe0c258237dd9db473f76ef5274a4d
- Size of remote file:
- 1.34 GB
- SHA256:
- c16330ce858afb0d262a56af407fc54f9e63d6aab7582cbbd03cea7e5cf387f5
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