Instructions to use ModelSpace/GemmaX2-28-2B-Pretrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelSpace/GemmaX2-28-2B-Pretrain with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" 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("translation", model="ModelSpace/GemmaX2-28-2B-Pretrain")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ModelSpace/GemmaX2-28-2B-Pretrain") model = AutoModelForCausalLM.from_pretrained("ModelSpace/GemmaX2-28-2B-Pretrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ModelSpace/GemmaX2-28-2B-Pretrain: direct link, hf CLI and curl.
- Browser
- Download file 17.5 MB
-
https://huggingface.co/ModelSpace/GemmaX2-28-2B-Pretrain/resolve/main/tokenizer.json
- Command line
-
hf download hf://ModelSpace/GemmaX2-28-2B-Pretrain/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ModelSpace/GemmaX2-28-2B-Pretrain/resolve/main/tokenizer.json
17.5 MB
- Xet hash:
- 468f89786a084f976ebe64a0fb2ecf73029025701e08d5a125aa4239fff2908e
- Size of remote file:
- 17.5 MB
- SHA256:
- 3f289bc05132635a8bc7aca7aa21255efd5e18f3710f43e3cdb96bcd41be4922
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