Translation
Transformers
Safetensors
JAX
t5
text2text-generation
text-generation-inference
8-bit precision
bitsandbytes
Instructions to use Emilio407/madlad400-7b-mt-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Emilio407/madlad400-7b-mt-8bit 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="Emilio407/madlad400-7b-mt-8bit")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Emilio407/madlad400-7b-mt-8bit") model = AutoModelForSeq2SeqLM.from_pretrained("Emilio407/madlad400-7b-mt-8bit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc827a0db929e5dc70fda4c0f3aaf27d3cc0d7e58565c72dfb893d304aa19b2f
- Size of remote file:
- 16.6 MB
- SHA256:
- 03f5d7dc88da0cb4bb6b7a1d9d66ee62f5bd339ef0aaaf6e89d74829df5830c0
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