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:
- 446e378a4e9199660ac0ce7f13102d7cb28c76a667a0bf3540c187616bb4f772
- Size of remote file:
- 459 kB
- SHA256:
- 35745fd2c3eb3466c5efd0ca19002d98dbdda3612fd54c84ba76c94f243749c7
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