Instructions to use nttx/4e65dfe5-e77f-42e6-9a9f-bd0dba0b0237 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nttx/4e65dfe5-e77f-42e6-9a9f-bd0dba0b0237 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "nttx/4e65dfe5-e77f-42e6-9a9f-bd0dba0b0237") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2700, checkpoint
Browse files
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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{
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"best_metric": 11.
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"best_model_checkpoint": "miner_id_24/checkpoint-
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"epoch": 4.
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"eval_steps": 300,
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"global_step":
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"is_world_process_zero": true,
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"eval_samples_per_second": 209.202,
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"eval_steps_per_second": 26.228,
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"step": 2400
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}
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"logging_steps": 300,
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"attributes": {}
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"total_flos":
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"train_batch_size": 8,
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"trial_name": null,
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"trial_params": null
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{
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"best_metric": 11.912158012390137,
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"best_model_checkpoint": "miner_id_24/checkpoint-2700",
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"epoch": 4.511792945105406,
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"eval_steps": 300,
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"global_step": 2700,
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"eval_samples_per_second": 209.202,
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"eval_steps_per_second": 26.228,
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"step": 2400
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},
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{
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"epoch": 4.511792945105406,
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"grad_norm": 0.012792945839464664,
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"learning_rate": 1.0469365763439531e-05,
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"loss": 11.9128,
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"step": 2700
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{
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"epoch": 4.511792945105406,
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"eval_loss": 11.912158012390137,
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"eval_runtime": 9.6282,
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"eval_samples_per_second": 209.592,
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"eval_steps_per_second": 26.277,
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"step": 2700
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"logging_steps": 300,
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"attributes": {}
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"train_batch_size": 8,
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