Instructions to use diaenra/1dea7484-05cd-4c06-b678-3f1012e839ba with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use diaenra/1dea7484-05cd-4c06-b678-3f1012e839ba with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta") model = PeftModel.from_pretrained(base_model, "diaenra/1dea7484-05cd-4c06-b678-3f1012e839ba") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 351, checkpoint
Browse files
last-checkpoint/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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size 1720044440
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version https://git-lfs.github.com/spec/v1
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oid sha256:076af47d7078327fdcddbb6d8fc9040b2f10aea9193be908e14f3d5b5ca2d65c
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size 1720044440
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last-checkpoint/rng_state.pth
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version https://git-lfs.github.com/spec/v1
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size 14244
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version https://git-lfs.github.com/spec/v1
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oid sha256:fe62285d37cb7ae2f76e17d237cec158f486f0d7fd385eb64625216b53c53bd6
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size 14244
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last-checkpoint/scheduler.pt
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version https://git-lfs.github.com/spec/v1
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size 1064
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version https://git-lfs.github.com/spec/v1
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oid sha256:6cfc2996c76931e741c35f64ea4489062ec8d7b0dac2fcacee62f28292fc1fdc
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size 1064
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last-checkpoint/trainer_state.json
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{
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"best_metric": null,
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"best_model_checkpoint": null,
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-
"epoch": 0.
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"eval_steps": 500,
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-
"global_step":
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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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"learning_rate": 4.159163858762254e-05,
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"loss": 0.0,
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"step": 239
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| 1683 |
}
|
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