Instructions to use vaibkumar/agentic_training_finetuned_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vaibkumar/agentic_training_finetuned_v3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vaibkumar/agentic_training_finetuned_v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from vaibkumar/agentic_training_finetuned_v3: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/vaibkumar/agentic_training_finetuned_v3/resolve/main/tokenizer.json
- Command line
-
hf download hf://vaibkumar/agentic_training_finetuned_v3/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/vaibkumar/agentic_training_finetuned_v3/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 183feaf3854ea652c1087520f20fdc39282f652edf10541e6904a3d3f975425e
- Size of remote file:
- 17.1 MB
- SHA256:
- b0240ce510f08e6c2041724e9043e33be9d251d1e4a4d94eb68cd47b954b61d2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.