Instructions to use Saeedabdf/gemma2-27b-biomedical-5k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Saeedabdf/gemma2-27b-biomedical-5k with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-27b-it") model = PeftModel.from_pretrained(base_model, "Saeedabdf/gemma2-27b-biomedical-5k") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1084, checkpoint
Browse files
last-checkpoint/adapter_config.json
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"task_type": "CAUSAL_LM",
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"q_proj",
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"up_proj",
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"k_proj"
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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last-checkpoint/adapter_model.safetensors
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last-checkpoint/optimizer.pt
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last-checkpoint/rng_state.pth
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last-checkpoint/scheduler.pt
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last-checkpoint/trainer_state.json
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"best_model_checkpoint": "/checkpoints/gemma2-27b-biomedical/checkpoint-500",
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"logging_steps": 20,
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last-checkpoint/training_args.bin
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