Add runpod sls handler (#2530) [skip ci]
* Add runpod sls handler * remove LICENSE and fix README * chore: lint * use axolotl cloud image as base and various fixes * fix: trim allowed cuda versions * restore dockerfile * chore: update title * use axolotl cloud image --------- Co-authored-by: Wing Lian <wing@axolotl.ai> Co-authored-by: NanoCode012 <nano@axolotl.ai>
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.runpod/src/test_input.json
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61
.runpod/src/test_input.json
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{
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"input": {
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"user_id": "user",
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"model_id": "llama-test",
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"run_id": "llama-test",
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"credentials": {
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"wandb_api_key": "",
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"hf_token": ""
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},
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"args": {
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"base_model": "NousResearch/Meta-Llama-3-8B",
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"model_type": "LlamaForCausalLM",
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"tokenizer_type": "AutoTokenizer",
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"load_in_8bit": true,
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"load_in_4bit": false,
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"strict": false,
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"datasets": [
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{
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"path": "mhenrichsen/alpaca_2k_test",
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"type": "alpaca"
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}
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],
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"val_set_size": 0.05,
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"output_dir": "./outputs/lora-out",
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"sequence_len": 4096,
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"sample_packing": true,
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"eval_sample_packing": false,
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"pad_to_sequence_len": true,
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"adapter": "lora",
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"lora_r": 32,
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"lora_alpha": 16,
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"lora_dropout": 0.05,
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"lora_target_linear": true,
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"lora_modules_to_save": [
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"embed_tokens",
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"lm_head"
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],
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"gradient_accumulation_steps": 4,
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"micro_batch_size": 2,
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"num_epochs": 1,
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"optimizer": "adamw_bnb_8bit",
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"lr_scheduler": "cosine",
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"learning_rate": 0.0002,
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"train_on_inputs": false,
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"group_by_length": false,
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"bf16": "auto",
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"tf32": false,
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"gradient_checkpointing": true,
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"logging_steps": 1,
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"flash_attention": true,
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"warmup_steps": 1,
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"evals_per_epoch": 1,
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"eval_max_new_tokens": 128,
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"saves_per_epoch": 1,
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"weight_decay": 0.0,
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"special_tokens": {
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"pad_token": "<|end_of_text|>"
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}
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}
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}
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}
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