!pip install git+https://www.github.com/huggingface/transformers

!pip install git+https://github.com/huggingface/accelerate

!pip install bitsandbytes

!pip install einops

from transformers import AutoModelForCausalLM, AutoConfig, AutoTokenizer
import torch

model_path="tiiuae/falcon-40b-instruct"

config = AutoConfig.from_pretrained(model_path, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_path, trust_remote_code=True, load_in_4bit=True, device_map="auto")

tokenizer = AutoTokenizer.from_pretrained("tiiuae/falcon-40b-instruct")

input_text = "Describe the solar system."
input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")

outputs = model.generate(input_ids, max_length=100)
print(tokenizer.decode(outputs[0]))

Collecting git+https://www.github.com/huggingface/transformers
  Cloning https://www.github.com/huggingface/transformers to /tmp/pip-req-build-6pyatvel
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Installing collected packages: tokenizers, safetensors, huggingface-hub, transformers
Successfully installed huggingface-hub-0.15.1 safetensors-0.3.1 tokenizers-0.13.3 transformers-4.31.0.dev0
Collecting git+https://github.com/huggingface/accelerate
  Cloning https://github.com/huggingface/accelerate to /tmp/pip-req-build-76ziff6x
  Running command git clone --filter=blob:none --quiet https://github.com/huggingface/accelerate /tmp/pip-req-build-76ziff6x
  Resolved https://github.com/huggingface/accelerate to commit d141b4ce794227450a105b7281611c7980e5b3d6
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Successfully built accelerate
Installing collected packages: accelerate
Successfully installed accelerate-0.21.0.dev0
Collecting bitsandbytes
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Installing collected packages: bitsandbytes
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Collecting einops
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A new version of the following files was downloaded from https://huggingface.co/tiiuae/falcon-40b-instruct:
- configuration_RW.py
. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.
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- modelling_RW.py
. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.
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===================================BUG REPORT===================================
Welcome to bitsandbytes. For bug reports, please run

python -m bitsandbytes

 and submit this information together with your error trace to: https://github.com/TimDettmers/bitsandbytes/issues
================================================================================
bin /usr/local/lib/python3.10/dist-packages/bitsandbytes/libbitsandbytes_cuda118.so
CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching in backup paths...
CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so
CUDA SETUP: Highest compute capability among GPUs detected: 8.0
CUDA SETUP: Detected CUDA version 118
CUDA SETUP: Loading binary /usr/local/lib/python3.10/dist-packages/bitsandbytes/libbitsandbytes_cuda118.so...
/usr/local/lib/python3.10/dist-packages/bitsandbytes/cuda_setup/main.py:149: UserWarning: /usr/lib64-nvidia did not contain ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] as expected! Searching further paths...
  warn(msg)
/usr/local/lib/python3.10/dist-packages/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/sys/fs/cgroup/memory.events /var/colab/cgroup/jupyter-children/memory.events')}
  warn(msg)
/usr/local/lib/python3.10/dist-packages/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//172.28.0.1'), PosixPath('8013'), PosixPath('http')}
  warn(msg)
/usr/local/lib/python3.10/dist-packages/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//colab.research.google.com/tun/m/cc48301118ce562b961b3c22d803539adc1e0c19/gpu-a100-s-b20acq94qsrp --tunnel_background_save_delay=10s --tunnel_periodic_background_save_frequency=30m0s --enable_output_coalescing=true --output_coalescing_required=true'), PosixPath('--logtostderr --listen_host=172.28.0.12 --target_host=172.28.0.12 --tunnel_background_save_url=https')}
  warn(msg)
/usr/local/lib/python3.10/dist-packages/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/env/python')}
  warn(msg)
/usr/local/lib/python3.10/dist-packages/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//ipykernel.pylab.backend_inline'), PosixPath('module')}
  warn(msg)
/usr/local/lib/python3.10/dist-packages/bitsandbytes/cuda_setup/main.py:149: UserWarning: Found duplicate ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] files: {PosixPath('/usr/local/cuda/lib64/libcudart.so'), PosixPath('/usr/local/cuda/lib64/libcudart.so.11.0')}.. We'll flip a coin and try one of these, in order to fail forward.
Either way, this might cause trouble in the future:
If you get `CUDA error: invalid device function` errors, the above might be the cause and the solution is to make sure only one ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] in the paths that we search based on your env.
  warn(msg)
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---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
[<ipython-input-1-c89997e10ae9>](https://localhost:8080/#) in <cell line: 15>()
     13 
     14 config = AutoConfig.from_pretrained(model_path, trust_remote_code=True)
---> 15 model = AutoModelForCausalLM.from_pretrained(model_path, trust_remote_code=True, load_in_4bit=True, device_map="auto")
     16 
     17 tokenizer = AutoTokenizer.from_pretrained("tiiuae/falcon-40b-instruct")

3 frames
[/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py](https://localhost:8080/#) in to(self, *args, **kwargs)
   1894         # Checks if the model has been loaded in 8-bit
   1895         if getattr(self, "is_quantized", False):
-> 1896             raise ValueError(
   1897                 "`.to` is not supported for `4-bit` or `8-bit` models. Please use the model as it is, since the"
   1898                 " model has already been set to the correct devices and casted to the correct `dtype`."

ValueError: `.to` is not supported for `4-bit` or `8-bit` models. Please use the model as it is, since the model has already been set to the correct devices and casted to the correct `dtype`.