Instructions to use evgmaslov/Mistral-Nemo-Instruct-2407-cars with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use evgmaslov/Mistral-Nemo-Instruct-2407-cars with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-Nemo-Instruct-2407") model = PeftModel.from_pretrained(base_model, "evgmaslov/Mistral-Nemo-Instruct-2407-cars") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 400, checkpoint
Browse files- last-checkpoint/adapter_model.safetensors +1 -1
- last-checkpoint/optimizer.pt +1 -1
- last-checkpoint/rng_state_0.pth +1 -1
- last-checkpoint/rng_state_1.pth +1 -1
- last-checkpoint/rng_state_2.pth +1 -1
- last-checkpoint/rng_state_3.pth +1 -1
- last-checkpoint/rng_state_4.pth +1 -1
- last-checkpoint/rng_state_5.pth +1 -1
- last-checkpoint/rng_state_6.pth +1 -1
- last-checkpoint/rng_state_7.pth +1 -1
- last-checkpoint/scheduler.pt +1 -1
- last-checkpoint/trainer_state.json +13 -5
last-checkpoint/adapter_model.safetensors
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last-checkpoint/trainer_state.json
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{
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"best_metric": 0.
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"best_model_checkpoint": "evgmaslov/Mistral-Nemo-Instruct-2407-cars/checkpoint-
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"eval_steps": 100,
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"logging_steps": 500,
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