Instructions to use BSC-LT/salamandraTA-7b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BSC-LT/salamandraTA-7b-instruct 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="BSC-LT/salamandraTA-7b-instruct")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BSC-LT/salamandraTA-7b-instruct") model = AutoModelForCausalLM.from_pretrained("BSC-LT/salamandraTA-7b-instruct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a1449504a10eb5a0e4767f16a840272779ae784fe863054a6609c8a510aa844
- Size of remote file:
- 15.7 MB
- SHA256:
- acf96cf1b7d4c079d9f94e4a51d1c0468e58a974b3ac360a52bf9d4a978d39dd
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