Translation
Transformers
Safetensors
llama
text-generation
multilingual
machine-translation
reinforcement-learning
text-generation-inference
Instructions to use lyf07/LLaMAX3-8B-Alpaca-WALAR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lyf07/LLaMAX3-8B-Alpaca-WALAR 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="lyf07/LLaMAX3-8B-Alpaca-WALAR")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("lyf07/LLaMAX3-8B-Alpaca-WALAR") model = AutoModelForCausalLM.from_pretrained("lyf07/LLaMAX3-8B-Alpaca-WALAR") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 7ede80767b1befe44fadbe4e97bee41c8988469bfaaaf9b3a61f3b2712b3cc6f
- Size of remote file:
- 261 kB
- SHA256:
- ce61157495f0387036646abc36df0f80bafca71e97fa2eef1fb8dbdfeccedeec
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