Translation
Transformers
Safetensors
gemma3_text
text-generation
wmt26
model-compression
machine-translation
gemma
compressed-tensors
vllm
text-generation-inference
Instructions to use soksof/gemma-3-12b-wmt26-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use soksof/gemma-3-12b-wmt26-fp8 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="soksof/gemma-3-12b-wmt26-fp8")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("soksof/gemma-3-12b-wmt26-fp8") model = AutoModelForCausalLM.from_pretrained("soksof/gemma-3-12b-wmt26-fp8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4c7aa84fb94a696d78f2bde62590a25b6741b7365ed842f9310b5dcab71d95d
- Size of remote file:
- 33.4 MB
- SHA256:
- 4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
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