Instructions to use haraygese/fastchat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use haraygese/fastchat with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("lmsys/fastchat-t5-3b-v1.0") model = PeftModel.from_pretrained(base_model, "haraygese/fastchat") - Notebooks
- Google Colab
- Kaggle
Upload model
#1
by faria-aupee - opened
- adapter_config.json +18 -0
- adapter_model.bin +3 -0
adapter_config.json
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{
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"base_model_name_or_path": "lmsys/fastchat-t5-3b-v1.0",
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"bias": "none",
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"enable_lora": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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"lora_alpha": 32,
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"lora_dropout": 0.05,
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"merge_weights": false,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 16,
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"target_modules": [
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"q",
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"v"
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],
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"task_type": "SEQ_2_SEQ_LM"
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}
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:add5125130e9c5d93dcf290f6e6811fdb7bc0e0bd63e5df120d416269c2237f9
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size 37854797
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