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:
- 25f9ad430b9206cdef60e324af3da3231caaab8ce1325e423e34c37bfaad4369
- Size of remote file:
- 4.98 GB
- SHA256:
- e1a7f08334f05a3672a2697f6801ef34a549b491167e13d4a06944946824dd76
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