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 training_args.bin from NPCProgrammer/ALBERT_Tweet_tuned: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/NPCProgrammer/ALBERT_Tweet_tuned/resolve/e8a6018cf6040e6ea09e54e1e40e82facfecb6a4/training_args.bin
- Command line
-
hf download hf://NPCProgrammer/ALBERT_Tweet_tuned@e8a6018cf6040e6ea09e54e1e40e82facfecb6a4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/NPCProgrammer/ALBERT_Tweet_tuned/resolve/e8a6018cf6040e6ea09e54e1e40e82facfecb6a4/training_args.bin
4.92 kB
- Xet hash:
- 2850bbb97b1c2b34621a9fba6b77071334c237772fa94331e83c9d5e432eae19
- Size of remote file:
- 4.92 kB
- SHA256:
- 86d4cbfe1a23de1a44e006d1c89ba3e7419786f02eb464c024fd864358fd9846
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