Instructions to use onnookk/trainer_init_with_head_batch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use onnookk/trainer_init_with_head_batch with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, LlamaForCausalLM_bpe tokenizer = AutoTokenizer.from_pretrained("onnookk/trainer_init_with_head_batch") model = LlamaForCausalLM_bpe.from_pretrained("onnookk/trainer_init_with_head_batch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from onnookk/trainer_init_with_head_batch: direct link, hf CLI and curl.
- Browser
- Download file 517 kB
-
https://huggingface.co/onnookk/trainer_init_with_head_batch/resolve/main/tokenizer.model
- Command line
-
hf download hf://onnookk/trainer_init_with_head_batch/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/onnookk/trainer_init_with_head_batch/resolve/main/tokenizer.model
517 kB
- Xet hash:
- f0538707c19a232f49e33dfd6217828dd2e8da1c679a60c48f20afb4e4d1a083
- Size of remote file:
- 517 kB
- SHA256:
- 2a170f21f94d07931dae996c3f0375b0cfc74ba9852e551ed0480893f19ef2b0
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