Feature Extraction
Transformers
Safetensors
internlm2
llama-factory
full
Generated from Trainer
custom_code
Instructions to use anthonymeo/full-train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anthonymeo/full-train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="anthonymeo/full-train", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("anthonymeo/full-train", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from anthonymeo/full-train: direct link, hf CLI and curl.
- Browser
- Download file 7.1 kB
-
https://huggingface.co/anthonymeo/full-train/resolve/main/training_args.bin
- Command line
-
hf download hf://anthonymeo/full-train/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/anthonymeo/full-train/resolve/main/training_args.bin
7.1 kB
- Xet hash:
- 7191c7c0ae7727256be07961aa760f820c62c9add6fb9c6f979cbd4745be379b
- Size of remote file:
- 7.1 kB
- SHA256:
- 9a53c59ed2fac14ba109a5ef128690cabe027e77f0b8f43bc88f5dec4430d4f7
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