text: Title: Inappropriate saving of the merged fine tuned llama-2 model
  Body: Hi,
  I am trying to fine tune the llama-2 model with the help of the following config file->
  ``` model_type: llm
  base_model: /home/ubuntu/llama-2-7b-hf_for_merge
  
  quantization:
    bits: 8
  
  adapter:
    type: lora
    r: 8
    dropout: 0.05
    target_modules: null
    alpha: 16
    pretrained_adapter_weights: null
    postprocessor:
        merge_adapter_into_base_model: true
        progressbar: true
    bias_type: none
  
  prompt:
    template: |
      ### Instruction:
      {Instruction}
  
      ### Context:
      {Context}
  
      ### Response:
  
  
  input_features:
    - name: prompt
      type: text
      preprocessing:
        max_sequence_length: 1024
  
  output_features:
    - name: Response
      type: text
      preprocessing:
        max_sequence_length: 512
  
  trainer:
    type: finetune
    learning_rate: 0.0001
    batch_size: 1
    max_batch_size: 1
    gradient_accumulation_steps: 1
    enable_gradient_checkpointing: true
    epochs: 3
    learning_rate_scheduler:
      warmup_fraction: 0.01
  
  preprocessing:
    sample_ratio: 1.0
  
  backend:
    type: local
  ```
  The fine tuning is successful and I can see that merge and unload process was also completed as shown->
  
  ```
  Unloading and merging model:   0%|          | 0/518 [00:00<?, ?it/s]/opt/conda/envs/ludwig_train_env/lib/python3.10/site-packages/peft/tuners/lora/bnb.py:67: UserWarning: Merge lora module to 8-bit linear may get different generations due to rounding errors.
    warnings.warn(
  
  Unloading and merging model:   1%|▏         | 7/518 [00:00<00:07, 66.47it/s]
  Unloading and merging model:   4%|▍         | 23/518 [00:00<00:06, 80.72it/s]
  Unloading and merging model:   8%|▊         | 39/518 [00:00<00:05, 84.70it/s]
  Unloading and merging model:  11%|█         | 55/518 [00:00<00:05, 86.39it/s]
  Unloading and merging model:  14%|█▎        | 71/518 [00:00<00:05, 87.25it/s]
  Unloading and merging model:  17%|█▋        | 87/518 [00:01<00:04, 87.56it/s]
  Unloading and merging model:  20%|█▉        | 103/518 [00:01<00:04, 87.93it/s]
  Unloading and merging model:  23%|██▎       | 119/518 [00:01<00:04, 87.98it/s]
  Unloading and merging model:  26%|██▌       | 135/518 [00:01<00:04, 88.05it/s]
  Unloading and merging model:  29%|██▉       | 151/518 [00:01<00:04, 88.08it/s]
  Unloading and merging model:  32%|███▏      | 167/518 [00:01<00:03, 88.15it/s]
  Unloading and merging model:  35%|███▌      | 183/518 [00:02<00:03, 87.92it/s]
  Unloading and merging model:  38%|███▊      | 199/518 [00:02<00:03, 87.75it/s]
  Unloading and merging model:  42%|████▏     | 215/518 [00:02<00:03, 87.50it/s]
  Unloading and merging model:  45%|████▍     | 231/518 [00:02<00:03, 87.44it/s]
  Unloading and merging model:  48%|████▊     | 247/518 [00:02<00:03, 87.47it/s]
  Unloading and merging model:  51%|█████     | 263/518 [00:03<00:02, 87.39it/s]
  Unloading and merging model:  54%|█████▍    | 279/518 [00:03<00:02, 87.43it/s]
  Unloading and merging model:  57%|█████▋    | 295/518 [00:03<00:02, 87.35it/s]
  Unloading and merging model:  60%|██████    | 311/518 [00:03<00:02, 87.30it/s]
  Unloading and merging model:  63%|██████▎   | 327/518 [00:03<00:02, 87.31it/s]
  Unloading and merging model:  66%|██████▌   | 343/518 [00:03<00:02, 87.48it/s]
  Unloading and merging model:  69%|██████▉   | 359/518 [00:04<00:01, 87.61it/s]
  Unloading and merging model:  72%|███████▏  | 375/518 [00:04<00:01, 87.59it/s]
  Unloading and merging model:  75%|███████▌  | 391/518 [00:04<00:01, 87.64it/s]
  Unloading and merging model:  79%|███████▊  | 407/518 [00:04<00:01, 87.65it/s]
  Unloading and merging model:  82%|████████▏ | 423/518 [00:04<00:01, 87.69it/s]
  Unloading and merging model:  85%|████████▍ | 439/518 [00:05<00:00, 87.76it/s]
  Unloading and merging model:  88%|████████▊ | 455/518 [00:05<00:00, 87.79it/s]
  Unloading and merging model:  91%|█████████ | 471/518 [00:05<00:00, 87.74it/s]
  Unloading and merging model:  94%|█████████▍| 487/518 [00:05<00:00, 87.77it/s]
  Unloading and merging model:  97%|█████████▋| 503/518 [00:05<00:00, 87.75it/s]
  Unloading and merging model: 100%|██████████| 518/518 [00:05<00:00, 88.56it/s]
  Removed shared tensor {'model.layers.7.self_attn.o_proj.weight_format', 'model.layers.17.self_attn.q_proj.weight_format', 'model.layers.19.self_attn.o_proj.weight_format', 'model.layers.20.mlp.down_proj.weight_format', 'model.layers.21.mlp.down_proj.weight_format', 'model.layers.17.self_attn.v_proj.weight_format', 'model.layers.2.self_attn.v_proj.weight_format', 'model.layers.29.self_attn.o_proj.weight_format', 'model.layers.14.mlp.down_proj.weight_format', 'model.layers.27.mlp.up_proj.weight_format', 'model.layers.0.mlp.gate_proj.weight_format', 'model.layers.27.self_attn.k_proj.weight_format', 'model.layers.12.mlp.up_proj.weight_format', 'model.layers.30.mlp.gate_proj.weight_format', 'model.layers.8.mlp.down_proj.weight_format', 'model.layers.27.self_attn.q_proj.weight_format', 'model.layers.6.mlp.gate_proj.weight_format', 'model.layers.24.mlp.gate_proj.weight_format', 'model.layers.1.self_attn.v_proj.weight_format', 'model.layers.21.mlp.gate_proj.weight_format', 'model.layers.30.mlp.down_proj.weight_format', 'model.layers.15.mlp.up_proj.weight_format', 'model.layers.11.mlp.down_proj.weight_format', 'model.layers.10.mlp.gate_proj.weight_format', 'model.layers.24.self_attn.v_proj.weight_format', 'model.layers.29.mlp.gate_proj.weight_format', 'model.layers.17.mlp.gate_proj.weight_format', 'model.layers.8.self_attn.k_proj.weight_format', 'model.layers.21.self_attn.k_proj.weight_format', 'model.layers.14.self_attn.v_proj.weight_format', 'model.layers.4.self_attn.q_proj.weight_format', 'model.layers.0.mlp.up_proj.weight_format', 'model.layers.12.self_attn.q_proj.weight_format', 'model.layers.26.self_attn.q_proj.weight_format', 'model.layers.15.self_attn.k_proj.weight_format', 'model.layers.2.self_attn.q_proj.weight_format', 'model.layers.15.mlp.down_proj.weight_format', 'model.layers.5.self_attn.k_proj.weight_format', 'model.layers.20.self_attn.o_proj.weight_format', 'model.layers.6.mlp.down_proj.weight_format', 'model.layers.14.self_attn.k_proj.weight_format', 'model.layers.30.self_attn.v_proj.weight_format', 'model.layers.5.mlp.up_proj.weight_format', 'model.layers.22.self_attn.v_proj.weight_format', 'model.layers.28.self_attn.o_proj.weight_format', 'model.layers.9.mlp.gate_proj.weight_format', 'model.layers.18.mlp.down_proj.weight_format', 'model.layers.13.mlp.down_proj.weight_format', 'model.layers.8.self_attn.q_proj.weight_format', 'model.layers.13.self_attn.q_proj.weight_format', 'model.layers.27.mlp.gate_proj.weight_format', 'model.layers.3.self_attn.k_proj.weight_format', 'model.layers.8.mlp.gate_proj.weight_format', 'model.layers.12.mlp.down_proj.weight_format', 'model.layers.16.self_attn.o_proj.weight_format', 'model.layers.28.mlp.down_proj.weight_format', 'model.layers.30.self_attn.k_proj.weight_format', 'model.layers.31.mlp.up_proj.weight_format', 'model.layers.20.mlp.up_proj.weight_format', 'model.layers.16.self_attn.k_proj.weight_format', 'model.layers.30.self_attn.q_proj.weight_format', 'model.layers.11.mlp.up_proj.weight_format', 'model.layers.3.self_attn.o_proj.weight_format', 'model.layers.0.self_attn.v_proj.weight_format', 'model.layers.5.mlp.gate_proj.weight_format', 'model.layers.7.self_attn.v_proj.weight_format', 'model.layers.22.mlp.up_proj.weight_format', 'model.layers.17.self_attn.o_proj.weight_format', 'model.layers.4.self_attn.k_proj.weight_format', 'model.layers.25.self_attn.k_proj.weight_format', 'model.layers.5.self_attn.o_proj.weight_format', 'model.layers.15.self_attn.v_proj.weight_format', 'model.layers.2.mlp.down_proj.weight_format', 'model.layers.19.mlp.up_proj.weight_format', 'model.layers.11.self_attn.q_proj.weight_format', 'model.layers.3.self_attn.v_proj.weight_format', 'model.layers.9.self_attn.k_proj.weight_format', 'model.layers.11.mlp.gate_proj.weight_format', 'model.layers.17.mlp.up_proj.weight_format', 'model.layers.10.self_attn.q_proj.weight_format', 'model.layers.20.self_attn.k_proj.weight_format', 'model.layers.5.mlp.down_proj.weight_format', 'model.layers.23.mlp.gate_proj.weight_format', 'model.layers.23.mlp.down_proj.weight_format', 'model.layers.25.mlp.gate_proj.weight_format', 'model.layers.26.mlp.down_proj.weight_format', 'model.layers.4.mlp.down_proj.weight_format', 'model.layers.14.mlp.gate_proj.weight_format', 'model.layers.27.self_attn.v_proj.weight_format', 'model.layers.1.mlp.gate_proj.weight_format', 'model.layers.17.mlp.down_proj.weight_format', 'model.layers.20.mlp.gate_proj.weight_format', 'model.layers.1.mlp.up_proj.weight_format', 'model.layers.27.self_attn.o_proj.weight_format', 'model.layers.24.mlp.up_proj.weight_format', 'model.layers.10.self_attn.k_proj.weight_format', 'model.layers.18.mlp.gate_proj.weight_format', 'model.layers.13.self_attn.v_proj.weight_format', 'model.layers.18.self_attn.o_proj.weight_format', 'model.layers.15.mlp.gate_proj.weight_format', 'model.layers.16.self_attn.v_proj.weight_format', 'model.layers.23.self_attn.q_proj.weight_format', 'model.layers.12.self_attn.o_proj.weight_format', 'model.layers.23.mlp.up_proj.weight_format', 'model.layers.9.self_attn.q_proj.weight_format', 'model.layers.21.self_attn.q_proj.weight_format', 'model.layers.3.mlp.gate_proj.weight_format', 'model.layers.19.mlp.gate_proj.weight_format', 'model.layers.27.mlp.down_proj.weight_format', 'model.layers.10.mlp.up_proj.weight_format', 'model.layers.21.self_attn.o_proj.weight_format', 'model.layers.5.self_attn.v_proj.weight_format', 'model.layers.28.mlp.gate_proj.weight_format', 'model.layers.18.self_attn.v_proj.weight_format', 'model.layers.20.self_attn.v_proj.weight_format', 'model.layers.22.mlp.gate_proj.weight_format', 'model.layers.10.mlp.down_proj.weight_format', 'model.layers.1.self_attn.o_proj.weight_format', 'model.layers.4.mlp.gate_proj.weight_format', 'model.layers.21.self_attn.v_proj.weight_format', 'model.layers.28.mlp.up_proj.weight_format', 'model.layers.1.self_attn.q_proj.weight_format', 'model.layers.16.mlp.gate_proj.weight_format', 'model.layers.20.self_attn.q_proj.weight_format', 'model.layers.26.mlp.up_proj.weight_format', 'model.layers.8.self_attn.v_proj.weight_format', 'model.layers.30.self_attn.o_proj.weight_format', 'model.layers.30.mlp.up_proj.weight_format', 'model.layers.7.mlp.down_proj.weight_format', 'model.layers.4.self_attn.o_proj.weight_format', 'model.layers.21.mlp.up_proj.weight_format', 'model.layers.1.mlp.down_proj.weight_format', 'model.layers.19.self_attn.k_proj.weight_format', 'model.layers.8.self_attn.o_proj.weight_format', 'model.layers.15.self_attn.q_proj.weight_format', 'model.layers.23.self_attn.o_proj.weight_format', 'model.layers.6.mlp.up_proj.weight_format', 'model.layers.16.mlp.up_proj.weight_format', 'model.layers.19.self_attn.v_proj.weight_format', 'model.layers.29.mlp.down_proj.weight_format', 'model.layers.31.mlp.gate_proj.weight_format', 'model.layers.18.self_attn.q_proj.weight_format', 'model.layers.19.mlp.down_proj.weight_format', 'model.layers.0.self_attn.o_proj.weight_format', 'model.layers.2.mlp.gate_proj.weight_format', 'model.layers.23.self_attn.k_proj.weight_format', 'model.layers.29.self_attn.q_proj.weight_format', 'model.layers.10.self_attn.o_proj.weight_format', 'model.layers.25.self_attn.v_proj.weight_format', 'model.layers.13.self_attn.o_proj.weight_format', 'model.layers.25.self_attn.q_proj.weight_format', 'model.layers.12.mlp.gate_proj.weight_format', 'model.layers.0.mlp.down_proj.weight_format', 'model.layers.12.self_attn.v_proj.weight_format', 'model.layers.7.self_attn.q_proj.weight_format', 'model.layers.24.self_attn.k_proj.weight_format', 'model.layers.1.self_attn.k_proj.weight_format', 'model.layers.24.mlp.down_proj.weight_format', 'model.layers.31.self_attn.q_proj.weight_format', 'model.layers.11.self_attn.o_proj.weight_format', 'model.layers.22.mlp.down_proj.weight_format', 'model.layers.7.self_attn.k_proj.weight_format', 'model.layers.26.self_attn.o_proj.weight_format', 'model.layers.14.self_attn.o_proj.weight_format', 'model.layers.29.self_attn.k_proj.weight_format', 'model.layers.23.self_attn.v_proj.weight_format', 'model.layers.7.mlp.up_proj.weight_format', 'model.layers.2.self_attn.k_proj.weight_format', 'model.layers.3.mlp.up_proj.weight_format', 'model.layers.6.self_attn.k_proj.weight_format', 'model.layers.19.self_attn.q_proj.weight_format', 'model.layers.3.mlp.down_proj.weight_format', 'model.layers.7.mlp.gate_proj.weight_format', 'model.layers.22.self_attn.o_proj.weight_format', 'model.layers.2.self_attn.o_proj.weight_format', 'model.layers.0.self_attn.k_proj.weight_format', 'model.layers.29.self_attn.v_proj.weight_format', 'model.layers.24.self_attn.q_proj.weight_format', 'model.layers.4.mlp.up_proj.weight_format', 'model.layers.4.self_attn.v_proj.weight_format', 'model.layers.13.mlp.up_proj.weight_format', 'model.layers.25.self_attn.o_proj.weight_format', 'model.layers.10.self_attn.v_proj.weight_format', 'model.layers.28.self_attn.q_proj.weight_format', 'model.layers.5.self_attn.q_proj.weight_format', 'model.layers.6.self_attn.q_proj.weight_format', 'model.layers.14.self_attn.q_proj.weight_format', 'model.layers.9.self_attn.o_proj.weight_format', 'model.layers.15.self_attn.o_proj.weight_format', 'model.layers.26.self_attn.v_proj.weight_format', 'model.layers.13.mlp.gate_proj.weight_format', 'model.layers.28.self_attn.k_proj.weight_format', 'model.layers.9.self_attn.v_proj.weight_format', 'model.layers.31.self_attn.k_proj.weight_format', 'model.layers.31.mlp.down_proj.weight_format', 'model.layers.2.mlp.up_proj.weight_format', 'model.layers.9.mlp.down_proj.weight_format', 'model.layers.31.self_attn.v_proj.weight_format', 'model.layers.17.self_attn.k_proj.weight_format', 'model.layers.12.self_attn.k_proj.weight_format', 'model.layers.28.self_attn.v_proj.weight_format', 'model.layers.29.mlp.up_proj.weight_format', 'model.layers.26.mlp.gate_proj.weight_format', 'model.layers.8.mlp.up_proj.weight_format', 'model.layers.25.mlp.down_proj.weight_format', 'model.layers.11.self_attn.v_proj.weight_format', 'model.layers.26.self_attn.k_proj.weight_format', 'model.layers.6.self_attn.o_proj.weight_format', 'model.layers.24.self_attn.o_proj.weight_format', 'model.layers.9.mlp.up_proj.weight_format', 'model.layers.31.self_attn.o_proj.weight_format', 'model.layers.18.mlp.up_proj.weight_format', 'model.layers.16.mlp.down_proj.weight_format', 'model.layers.11.self_attn.k_proj.weight_format', 'model.layers.13.self_attn.k_proj.weight_format', 'model.layers.14.mlp.up_proj.weight_format', 'model.layers.22.self_attn.q_proj.weight_format', 'model.layers.22.self_attn.k_proj.weight_format', 'model.layers.6.self_attn.v_proj.weight_format', 'model.layers.3.self_attn.q_proj.weight_format', 'model.layers.25.mlp.up_proj.weight_format', 'model.layers.18.self_attn.k_proj.weight_format', 'model.layers.16.self_attn.q_proj.weight_format'} while saving. This should be OK, but check by verifying that you don't receive any warning while reloading
  
  ╒══════════╕
  │ FINISHED │
  ╘══════════╛
  
  Finetuning process has been completed..
  Saving the finetuned base model..
  Saving the finetuned base model completed..
  
  ```
  
  
  
  When I checked the disk size for this saved model it was 7.6MB only...indicating that the merge did not happen appropriately.
  
  Environment:
  ```
  absl-py==2.0.0
  accelerate==0.24.1
  aiohttp==3.8.6
  aiohttp-cors==0.7.0
  aiorwlock==1.4.0
  aiosignal==1.3.1
  anyio==4.2.0
  asttokens @ file:///home/conda/feedstock_root/build_artifacts/asttokens_1698341106958/work
  async-timeout==4.0.3
  attrs==23.1.0
  awscli==1.32.25
  backports.functools-lru-cache @ file:///home/conda/feedstock_root/build_artifacts/backports.functools_lru_cache_1687772187254/work
  beautifulsoup4==4.12.3
  bitsandbytes==0.40.2
  bleach==6.1.0
  blessed==1.20.0
  blinker==1.7.0
  blis==0.7.11
  botocore==1.34.25
  Brotli==1.1.0
  cachetools==5.3.2
  captum==0.7.0
  catalogue==2.0.10
  certifi==2023.7.22
  charset-normalizer==3.3.2
  click==8.1.7
  cloudpathlib==0.16.0
  cloudpickle==3.0.0
  colorama==0.4.4
  colorful==0.5.6
  comm @ file:///home/conda/feedstock_root/build_artifacts/comm_1691044910542/work
  commonmark==0.9.1
  confection==0.1.3
  contourpy==1.2.0
  cycler==0.12.1
  cymem==2.0.8
  Cython==3.0.5
  dask==2023.3.2
  dataclasses-json==0.6.2
  datasets==2.14.6
  debugpy @ file:///home/conda/feedstock_root/build_artifacts/debugpy_1695534290310/work
  decorator @ file:///home/conda/feedstock_root/build_artifacts/decorator_1641555617451/work
  deepspeed==0.12.3
  dill==0.3.7
  distlib==0.3.8
  docutils==0.16
  et-xmlfile==1.1.0
  exceptiongroup @ file:///home/conda/feedstock_root/build_artifacts/exceptiongroup_1692026125334/work
  executing @ file:///home/conda/feedstock_root/build_artifacts/executing_1698579936712/work
  faiss-cpu==1.7.4
  fastapi==0.109.0
  filelock==3.13.1
  Flask==3.0.1
  Flask-Compress==1.14
  fonttools==4.47.2
  frozenlist==1.4.0
  fsspec==2023.9.2
  future==0.18.3
  getdaft==0.1.20
  google-api-core==2.15.0
  google-auth==2.23.4
  google-auth-oauthlib==1.1.0
  googleapis-common-protos==1.62.0
  gpustat==1.1.1
  GPUtil==1.4.0
  grpcio==1.59.2
  h11==0.14.0
  h5py==3.10.0
  hiplot==0.1.33
  hjson==3.1.0
  html5lib==1.1
  httpcore==1.0.2
  httpx==0.26.0
  huggingface-hub==0.20.3
  hummingbird-ml==0.4.10
  hyperopt==0.2.7
  idna==3.4
  imagecodecs==2024.1.1
  importlib-metadata @ file:///home/conda/feedstock_root/build_artifacts/importlib-metadata_1688754491823/work
  ipykernel @ file:///home/conda/feedstock_root/build_artifacts/ipykernel_1698244021190/work
  ipython @ file:///home/conda/feedstock_root/build_artifacts/ipython_1698846603011/work
  ipywidgets==8.1.1
  itsdangerous==2.1.2
  jedi @ file:///home/conda/feedstock_root/build_artifacts/jedi_1696326070614/work
  Jinja2==3.1.2
  jmespath==1.0.1
  joblib==1.3.2
  jsonschema==4.6.2
  jupyter_client @ file:///home/conda/feedstock_root/build_artifacts/jupyter_client_1699283905679/work
  jupyter_core @ file:///home/conda/feedstock_root/build_artifacts/jupyter_core_1698673647019/work
  jupyterlab-widgets==3.0.9
  kaggle==1.5.16
  kiwisolver==1.4.5
  langcodes==3.3.0
  lightgbm==4.2.0
  lightgbm-ray==0.1.9
  lightning-utilities==0.9.0
  locket==1.0.0
  loguru==0.7.2
  loralib==0.1.2
  ludwig==0.9.3
  lxml==4.9.3
  Markdown==3.5.1
  MarkupSafe==2.1.3
  marshmallow==3.20.1
  marshmallow-dataclass==8.5.4
  marshmallow-jsonschema==0.13.0
  matplotlib==3.8.2
  matplotlib-inline @ file:///home/conda/feedstock_root/build_artifacts/matplotlib-inline_1660814786464/work
  mpi4py==3.1.5
  mpmath==1.3.0
  msgpack==1.0.7
  multidict==6.0.4
  multiprocess==0.70.15
  murmurhash==1.0.10
  mypy-extensions==1.0.0
  nest-asyncio @ file:///home/conda/feedstock_root/build_artifacts/nest-asyncio_1697083700168/work
  networkx==3.2.1
  ninja==1.11.1.1
  nltk==3.8.1
  numpy==1.26.2
  nvidia-cublas-cu12==12.1.3.1
  nvidia-cuda-cupti-cu12==12.1.105
  nvidia-cuda-nvrtc-cu12==12.1.105
  nvidia-cuda-runtime-cu12==12.1.105
  nvidia-cudnn-cu12==8.9.2.26
  nvidia-cufft-cu12==11.0.2.54
  nvidia-curand-cu12==10.3.2.106
  nvidia-cusolver-cu12==11.4.5.107
  nvidia-cusparse-cu12==12.1.0.106
  nvidia-ml-py==12.535.133
  nvidia-nccl-cu12==2.18.1
  nvidia-nvjitlink-cu12==12.3.52
  nvidia-nvtx-cu12==12.1.105
  oauthlib==3.2.2
  onnx==1.15.0
  onnxconverter-common==1.13.0
  opencensus==0.11.4
  opencensus-context==0.1.3
  openpyxl==3.1.2
  packaging @ file:///home/conda/feedstock_root/build_artifacts/packaging_1696202382185/work
  pandas==2.1.3
  parso @ file:///home/conda/feedstock_root/build_artifacts/parso_1638334955874/work
  partd==1.4.1
  peft==0.6.2
  pexpect @ file:///home/conda/feedstock_root/build_artifacts/pexpect_1667297516076/work
  pickleshare @ file:///home/conda/feedstock_root/build_artifacts/pickleshare_1602536217715/work
  Pillow==10.1.0
  platformdirs @ file:///home/conda/feedstock_root/build_artifacts/platformdirs_1699715570510/work
  preshed==3.0.9
  prometheus-client==0.19.0
  prompt-toolkit @ file:///home/conda/feedstock_root/build_artifacts/prompt-toolkit_1699963054032/work
  protobuf==3.20.3
  psutil==5.9.4
  ptitprince==0.2.7
  ptyprocess @ file:///home/conda/feedstock_root/build_artifacts/ptyprocess_1609419310487/work/dist/ptyprocess-0.7.0-py2.py3-none-any.whl
  pure-eval @ file:///home/conda/feedstock_root/build_artifacts/pure_eval_1642875951954/work
  py==1.11.0
  py-cpuinfo==9.0.0
  py-spy==0.3.14
  py4j==0.10.9.7
  pyarrow==14.0.1
  pyasn1==0.5.0
  pyasn1-modules==0.3.0
  pydantic==1.10.13
  Pygments @ file:///home/conda/feedstock_root/build_artifacts/pygments_1691408637400/work
  pynvml==11.5.0
  pyparsing==3.1.1
  pyrsistent==0.20.0
  python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1626286286081/work
  python-multipart==0.0.6
  python-slugify==8.0.1
  pytz==2023.3.post1
  pyxlsb==1.0.10
  PyYAML==6.0
  pyzmq @ file:///home/conda/feedstock_root/build_artifacts/pyzmq_1698062401223/work
  ray==2.3.1
  regex==2023.10.3
  requests==2.31.0
  requests-oauthlib==1.3.1
  retry==0.9.2
  rich==12.4.4
  rsa==4.7.2
  s3fs==0.4.2
  s3transfer==0.10.0
  sacremoses==0.1.1
  safetensors==0.4.2
  scikit-learn==1.3.2
  scipy==1.11.3
  seaborn==0.11.0
  sentence-transformers==2.2.2
  sentencepiece==0.1.99
  six @ file:///home/conda/feedstock_root/build_artifacts/six_1620240208055/work
  smart-open==6.4.0
  sniffio==1.3.0
  soupsieve==2.5
  spacy==3.7.2
  spacy-legacy==3.0.12
  spacy-loggers==1.0.5
  srsly==2.4.8
  stack-data @ file:///home/conda/feedstock_root/build_artifacts/stack_data_1669632077133/work
  starlette==0.35.1
  sympy==1.12
  tabulate==0.9.0
  tblib==3.0.0
  tensorboard==2.15.1
  tensorboard-data-server==0.7.2
  tensorboardX==2.2
  text-unidecode==1.3
  thinc==8.2.1
  threadpoolctl==3.2.0
  tifffile==2024.2.12
  tokenizers==0.15.2
  toolz==0.12.0
  torch==2.1.0
  torchaudio==2.1.0
  torchdata==0.7.0
  torchinfo==1.8.0
  torchmetrics==1.2.0
  torchtext==0.16.0
  torchvision==0.16.0
  tornado @ file:///home/conda/feedstock_root/build_artifacts/tornado_1695373560918/work
  tqdm==4.66.1
  traitlets @ file:///home/conda/feedstock_root/build_artifacts/traitlets_1698671135544/work
  transformers==4.37.2
  triton==2.1.0
  typer==0.9.0
  typing-inspect==0.9.0
  typing_extensions @ file:///home/conda/feedstock_root/build_artifacts/typing_extensions_1695040754690/work
  tzdata==2023.3
  urllib3==1.26.18
  uvicorn==0.27.0
  virtualenv==20.25.0
  wasabi==1.1.2
  wcwidth @ file:///home/conda/feedstock_root/build_artifacts/wcwidth_1699959196938/work
  weasel==0.3.4
  webencodings==0.5.1
  Werkzeug==3.0.1
  widgetsnbextension==4.0.9
  wrapt==1.16.0
  xgboost==2.0.3
  xgboost-ray==0.1.18
  xlrd==2.0.1
  XlsxWriter==3.1.9
  xlwt==1.3.0
  xxhash==3.4.1
  yarl==1.9.2
  zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1695255097490/work
  
  ```
  
  Can someone help me in solving this
  TIA
  
  