Instructions to use m-i/HY-MT1.5-1.8B-mlx-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m-i/HY-MT1.5-1.8B-mlx-fp16 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="m-i/HY-MT1.5-1.8B-mlx-fp16")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("m-i/HY-MT1.5-1.8B-mlx-fp16") model = AutoModelForCausalLM.from_pretrained("m-i/HY-MT1.5-1.8B-mlx-fp16") - MLX
How to use m-i/HY-MT1.5-1.8B-mlx-fp16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir HY-MT1.5-1.8B-mlx-fp16 m-i/HY-MT1.5-1.8B-mlx-fp16
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Upload special_tokens_map.json with huggingface_hub
Browse files- special_tokens_map.json +23 -0
special_tokens_map.json
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{
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"bos_token": {
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"content": "<|hy_begin▁of▁sentence|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "<|hy_place▁holder▁no▁2|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "<|hy_▁pad▁|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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