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lyf07
/
LLaMAX3-8B-Alpaca-WALAR

Translation
Transformers
Safetensors
llama
text-generation
multilingual
machine-translation
reinforcement-learning
text-generation-inference
Model card Files Files and versions
xet
Community
1

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", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
LLaMAX3-8B-Alpaca-WALAR
16.1 GB
Ctrl+K
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  • 3 contributors
History: 8 commits
lyf07's picture
lyf07
nielsr's picture
nielsr HF Staff
Add library_name and pipeline_tag metadata (#1)
fa5016e 5 months ago
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  • .gitattributes
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  • README.md
    4.28 kB
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  • chat_template.jinja
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  • config.json
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  • generation_config.json
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  • model-00001-of-00004.safetensors
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  • model-00002-of-00004.safetensors
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  • model-00003-of-00004.safetensors
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  • model-00004-of-00004.safetensors
    1.17 GB
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  • model.safetensors.index.json
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  • special_tokens_map.json
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  • tokenizer.json
    17.2 MB
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  • tokenizer_config.json
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