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-00004-of-00004.safetensors from NiuTrans/LMT-60-8B-Base: direct link, hf CLI and curl.
- Browser
- Download file 1.58 GB
-
https://huggingface.co/NiuTrans/LMT-60-8B-Base/resolve/main/model-00004-of-00004.safetensors
- Command line
-
hf download hf://NiuTrans/LMT-60-8B-Base/model-00004-of-00004.safetensors
-
curl -L -o model-00004-of-00004.safetensors https://huggingface.co/NiuTrans/LMT-60-8B-Base/resolve/main/model-00004-of-00004.safetensors
1.58 GB
- Xet hash:
- 15e6b6e74123ca41bb58cf7b5c4514228c55f284b511c1f8a95becb33cb32564
- Size of remote file:
- 1.58 GB
- SHA256:
- 99180ed6229522dc71e959eb8ab4686974ae894382736f86d2ce4d21eb02edfc
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