Instructions to use NiuTrans/LMT-60-8B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NiuTrans/LMT-60-8B-Base 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="NiuTrans/LMT-60-8B-Base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("NiuTrans/LMT-60-8B-Base") model = AutoModelForCausalLM.from_pretrained("NiuTrans/LMT-60-8B-Base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model-00003-of-00004.safetensors from NiuTrans/LMT-60-8B-Base: direct link, hf CLI and curl.
- Browser
- Download file 4.98 GB
-
https://huggingface.co/NiuTrans/LMT-60-8B-Base/resolve/main/model-00003-of-00004.safetensors
- Command line
-
hf download hf://NiuTrans/LMT-60-8B-Base/model-00003-of-00004.safetensors
-
curl -L -o model-00003-of-00004.safetensors https://huggingface.co/NiuTrans/LMT-60-8B-Base/resolve/main/model-00003-of-00004.safetensors
4.98 GB
- Xet hash:
- c6e2194f2519d4cd3bd2c8b7080341b54dcf3fe7fbd42efdd0731ba0b8dcd231
- Size of remote file:
- 4.98 GB
- SHA256:
- c65b35e47105aec89f2c813457e54dc27115b4f132c3f641f882f233143bc475
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