Text Classification
Transformers
PyTorch
English
bert
sentiment classification
sentiment analysis
text-embeddings-inference
Instructions to use himanshubeniwal/bert_cl_g_1700 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use himanshubeniwal/bert_cl_g_1700 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="himanshubeniwal/bert_cl_g_1700")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("himanshubeniwal/bert_cl_g_1700") model = AutoModelForSequenceClassification.from_pretrained("himanshubeniwal/bert_cl_g_1700", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from himanshubeniwal/bert_cl_g_1700: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/himanshubeniwal/bert_cl_g_1700/resolve/main/tokenizer.json
- Command line
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hf download hf://himanshubeniwal/bert_cl_g_1700/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/himanshubeniwal/bert_cl_g_1700/resolve/main/tokenizer.json
711 kB
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