Instructions to use mtzig/prm800k_qwen_alt_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mtzig/prm800k_qwen_alt_lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Math-7B-Instruct") model = PeftModel.from_pretrained(base_model, "mtzig/prm800k_qwen_alt_lora") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1000, checkpoint
Browse files- last-checkpoint/adapter_model.safetensors +1 -1
- last-checkpoint/global_step1000/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +3 -0
- last-checkpoint/global_step1000/bf16_zero_pp_rank_1_mp_rank_00_optim_states.pt +3 -0
- last-checkpoint/global_step1000/bf16_zero_pp_rank_2_mp_rank_00_optim_states.pt +3 -0
- last-checkpoint/global_step1000/bf16_zero_pp_rank_3_mp_rank_00_optim_states.pt +3 -0
- last-checkpoint/global_step1000/zero_pp_rank_0_mp_rank_00_model_states.pt +3 -0
- last-checkpoint/global_step1000/zero_pp_rank_1_mp_rank_00_model_states.pt +3 -0
- last-checkpoint/global_step1000/zero_pp_rank_2_mp_rank_00_model_states.pt +3 -0
- last-checkpoint/global_step1000/zero_pp_rank_3_mp_rank_00_model_states.pt +3 -0
- last-checkpoint/latest +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/scheduler.pt +1 -1
- last-checkpoint/trainer_state.json +0 -0
last-checkpoint/adapter_model.safetensors
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last-checkpoint/latest
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