Hello World! I am attempting to train my models on my own data. If I run the lora.py command using the 7b models from mistral or llama, it works fine. As soon as I upgrade to the larger models, I get an error File “/Users/conleysa/AI/MLX/mlx_venv/lib/python3.11/site-packages/mlx/nn/layers/base.py”, line 211, in load_weights
raise ValueError(f"Received parameters not in model: {extras}.")
I am using the Apple mlx python API on an M3 Max with 128GB RAM.
I get the exact same error running convert.py. The commands I have tried are:
python convert.py --hf-path mistralai/Mixtral-8x7B-Instruct-v0.1 -q
python lora.py --model mistralai/Mixtral-8x7B-Instruct-v0.1 --train --batch-size 1 --lora-layers 4
Same error both times. I’ll post the full error below but it’s ugly.
(mlx_venv) conleysa@M3Maximus lora % python lora.py --model meta-llama/Llama-2-13b-hf --train --batch-size 1 --lora-layers 4
Loading pretrained model
Fetching 11 files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 11/11 [00:00<00:00, 115922.97it/s]
Traceback (most recent call last):
File “/Users/conleysa/AI/MLX/mlx-examples/lora/lora.py”, line 321, in
model, tokenizer, _ = lora_utils.load(args.model)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/Users/conleysa/AI/MLX/mlx-examples/lora/utils.py”, line 140, in load
model.load_weights(list(weights.items()))
File “/Users/conleysa/AI/MLX/mlx_venv/lib/python3.11/site-packages/mlx/nn/layers/base.py”, line 211, in load_weights
raise ValueError(f"Received parameters not in model: {extras}.")
ValueError: Received parameters not in model: model.layers.38.self_attn.rotary_emb.inv_freq model.layers.33.self_attn.rotary_emb.inv_freq model.layers.0.self_attn.rotary_emb.inv_freq model.layers.9.self_attn.rotary_emb.inv_freq model.layers.36.self_attn.rotary_emb.inv_freq model.layers.5.self_attn.rotary_emb.inv_freq model.layers.18.self_attn.rotary_emb.inv_freq model.layers.6.self_attn.rotary_emb.inv_freq model.layers.31.self_attn.rotary_emb.inv_freq model.layers.13.self_attn.rotary_emb.inv_freq model.layers.30.self_attn.rotary_emb.inv_freq model.layers.29.self_attn.rotary_emb.inv_freq model.layers.23.self_attn.rotary_emb.inv_freq model.layers.8.self_attn.rotary_emb.inv_freq model.layers.25.self_attn.rotary_emb.inv_freq model.layers.20.self_attn.rotary_emb.inv_freq model.layers.15.self_attn.rotary_emb.inv_freq model.layers.28.self_attn.rotary_emb.inv_freq model.layers.19.self_attn.rotary_emb.inv_freq model.layers.12.self_attn.rotary_emb.inv_freq model.layers.32.self_attn.rotary_emb.inv_freq model.layers.7.self_attn.rotary_emb.inv_freq model.layers.34.self_attn.rotary_emb.inv_freq model.layers.37.self_attn.rotary_emb.inv_freq model.layers.26.self_attn.rotary_emb.inv_freq model.layers.22.self_attn.rotary_emb.inv_freq model.layers.24.self_attn.rotary_emb.inv_freq model.layers.16.self_attn.rotary_emb.inv_freq model.layers.4.self_attn.rotary_emb.inv_freq model.layers.2.self_attn.rotary_emb.inv_freq model.layers.39.self_attn.rotary_emb.inv_freq model.layers.11.self_attn.rotary_emb.inv_freq model.layers.21.self_attn.rotary_emb.inv_freq model.layers.27.self_attn.rotary_emb.inv_freq model.layers.3.self_attn.rotary_emb.inv_freq model.layers.1.self_attn.rotary_emb.inv_freq model.layers.14.self_attn.rotary_emb.inv_freq model.layers.17.self_attn.rotary_emb.inv_freq model.layers.10.self_attn.rotary_emb.inv_freq model.layers.35.self_attn.rotary_emb.inv_freq.
(mlx_venv) conleysa@M3Maximus lora %