Translation
Transformers
Safetensors
English
Chinese
llama
text-generation
text-generation-inference
Instructions to use Mxode/NanoTranslator-M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mxode/NanoTranslator-M 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="Mxode/NanoTranslator-M")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Mxode/NanoTranslator-M") model = AutoModelForCausalLM.from_pretrained("Mxode/NanoTranslator-M") - Notebooks
- Google Colab
- Kaggle
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| XL | 100 | LLaMA | SwiGLU |
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| L | 78 | LLaMA | GeGLU |
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| M2 | 22 | Qwen2 | GeGLU |
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| M | 22 | LLaMA | SwiGLU |
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| S | 9 | LLaMA | SwiGLU |
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| XS | 2 | LLaMA | SwiGLU |
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- **P.** - Parameters (in million)
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- **V.** - vocab size
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| Size | P. | Arch. | Act. | V. | H. | I. | L. | A.H. | K.H. | Tie |
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| XL | 100 | LLaMA | SwiGLU | 16K | 768 | 4096 | 8 | 24 | 8 | True |
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| L | 78 | LLaMA | GeGLU | 16K | 768 | 4096 | 6 | 24 | 8 | True |
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| M2 | 22 | Qwen2 | GeGLU | 4K | 432 | 2304 | 6 | 24 | 8 | True |
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| M | 22 | LLaMA | SwiGLU | 8K | 256 | 1408 | 16 | 16 | 4 | True |
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| S | 9 | LLaMA | SwiGLU | 4K | 168 | 896 | 16 | 12 | 4 | True |
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| XS | 2 | LLaMA | SwiGLU | 2K | 96 | 512 | 12 | 12 | 4 | True |
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- **P.** - Parameters (in million)
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- **V.** - vocab size
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