Instructions to use SalmonAI123/ViMrcbase-TFIDF-version-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SalmonAI123/ViMrcbase-TFIDF-version-1 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="SalmonAI123/ViMrcbase-TFIDF-version-1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("SalmonAI123/ViMrcbase-TFIDF-version-1") model = AutoModelForQuestionAnswering.from_pretrained("SalmonAI123/ViMrcbase-TFIDF-version-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from SalmonAI123/ViMrcbase-TFIDF-version-1: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/SalmonAI123/ViMrcbase-TFIDF-version-1/resolve/main/tokenizer.json
- Command line
-
hf download hf://SalmonAI123/ViMrcbase-TFIDF-version-1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/SalmonAI123/ViMrcbase-TFIDF-version-1/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- ba9c335b9be8af876447205e18e74052c09ef8261562241ebf760fba1abf1748
- Size of remote file:
- 17.1 MB
- SHA256:
- e5e8f0c8751780d4cbf163fb952d4fe95267c911dbb998f1bdb2f291cd82f020
路
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