Instructions to use NPCProgrammer/ALBERT_Tweet_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NPCProgrammer/ALBERT_Tweet_tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NPCProgrammer/ALBERT_Tweet_tuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NPCProgrammer/ALBERT_Tweet_tuned") model = AutoModelForSequenceClassification.from_pretrained("NPCProgrammer/ALBERT_Tweet_tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from NPCProgrammer/ALBERT_Tweet_tuned: direct link, hf CLI and curl.
- Browser
- Download file 46.7 MB
-
https://huggingface.co/NPCProgrammer/ALBERT_Tweet_tuned/resolve/main/model.safetensors
- Command line
-
hf download hf://NPCProgrammer/ALBERT_Tweet_tuned/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/NPCProgrammer/ALBERT_Tweet_tuned/resolve/main/model.safetensors
46.7 MB
- Xet hash:
- 9771c8f5455da695a0aeab7fba757c8226b0e228ff8f7eaa21be483d04907165
- Size of remote file:
- 46.7 MB
- SHA256:
- 5bdba054f097b83cb720ba1e9e3ff494475eab18d02ea9faa1567dd2ddfe1a85
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