Instructions to use DanielRegaladoCardoso/chart-reasoner-phi3-mini-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DanielRegaladoCardoso/chart-reasoner-phi3-mini-lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DanielRegaladoCardoso/chart-reasoner-phi3-mini-lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use DanielRegaladoCardoso/chart-reasoner-phi3-mini-lora with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DanielRegaladoCardoso/chart-reasoner-phi3-mini-lora to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DanielRegaladoCardoso/chart-reasoner-phi3-mini-lora to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for DanielRegaladoCardoso/chart-reasoner-phi3-mini-lora to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="DanielRegaladoCardoso/chart-reasoner-phi3-mini-lora", max_seq_length=2048, )
(Trained with Unsloth)
Browse files- tokenizer_config.json +3 -2
tokenizer_config.json
CHANGED
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@@ -12,5 +12,6 @@
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"sp_model_kwargs": {},
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"tokenizer_class": "TokenizersBackend",
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"unk_token": "<unk>",
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"use_default_system_prompt": false
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}
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"sp_model_kwargs": {},
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"tokenizer_class": "TokenizersBackend",
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"unk_token": "<unk>",
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"use_default_system_prompt": false,
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"chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{'<|system|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'user' %}{{'<|user|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'assistant' %}{{'<|assistant|>\n' + message['content'] + '<|end|>\n'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% else %}{{ eos_token }}{% endif %}"
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}
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