Instructions to use KingAsiedu/sentence_sentiments_analysis_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KingAsiedu/sentence_sentiments_analysis_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KingAsiedu/sentence_sentiments_analysis_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KingAsiedu/sentence_sentiments_analysis_bert") model = AutoModelForSequenceClassification.from_pretrained("KingAsiedu/sentence_sentiments_analysis_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from KingAsiedu/sentence_sentiments_analysis_bert: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/KingAsiedu/sentence_sentiments_analysis_bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://KingAsiedu/sentence_sentiments_analysis_bert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/KingAsiedu/sentence_sentiments_analysis_bert/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 84a55076fade9fb4f795fc963857b517f39f4d5cea8f851152f87d601a29c74b
- Size of remote file:
- 433 MB
- SHA256:
- d98833874b5b2a0da02e0b101b39d1dabf166392516ae64c214640ab17c9b781
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