Instructions to use am-infoweb/rap_phase2_11jan_15i_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use am-infoweb/rap_phase2_11jan_15i_v1 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="am-infoweb/rap_phase2_11jan_15i_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("am-infoweb/rap_phase2_11jan_15i_v1") model = AutoModelForQuestionAnswering.from_pretrained("am-infoweb/rap_phase2_11jan_15i_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from am-infoweb/rap_phase2_11jan_15i_v1: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/am-infoweb/rap_phase2_11jan_15i_v1/resolve/main/tokenizer.json
- Command line
-
hf download hf://am-infoweb/rap_phase2_11jan_15i_v1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/am-infoweb/rap_phase2_11jan_15i_v1/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 20c84e93d7572bd7ef26400d17026dccfbd9b41e53c6758e7a7d274bb9cbb859
- Size of remote file:
- 17.1 MB
- SHA256:
- 6ab204fa1b07a4334c9163b537ee092eca070bd56f4334976a8fd29119a68c23
路
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