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+title = "Running Vicuna-13B in the Cloud"
+date = 2023-05-06T00:00:00
+lastmod = 2023-05-06T00:00:00
+draft = false
+
+# Authors. Comma separated list, e.g. `["Bob Smith", "David Jones"]`.
+authors = ["Carl Pearson"]
+
+tags = []
+
+summary = ""
+
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+categories = []
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+
++++
+
+Vicuna-13B is an LLM based off of the LLaMa model.
+
+## Set up your Cloud Instance
+
+Create a cloud VM with
+* 150 GB of disk space
+* 64 GB of CPU memory
+
+When everything was done, my VM had 132GB of disk space used, so you'll probably want at least 150GB
+
+Ordinarily I wouldn't recommend setting up python like this, but since we're just experimenting:
+
+```
+apt-get install python3-pip
+```
+
+## Acquire the LLaMa-13B model
+
+For licensing reasons, Vicuna-13B is distributed as a delta of the LLaMa model, so the first step is to acquire the LLaMa model.
+The official way is to request the weights from Meta, by filling this [Google Docs form](https://docs.google.com/forms/d/e/1FAIpQLSfqNECQnMkycAp2jP4Z9TFX0cGR4uf7b_fBxjY_OjhJILlKGA/viewform?usp=send_form).
+
+You can also use leaked weights from a torrent with the following magnet link:
+
+`magnet:?xt=urn:btih:b8287ebfa04f<HASH>cf3e8014352&dn=LLaMA`
+
+> NOTE
+> replace `<HASH>` above with this: `879b048d4d4404108`
+
+Or, someone has made the leaked weights available on IPFS, which you can access through a helpful mirror:
+
+https://ipfs.io/ipfs/Qmb9y5GCkTG7ZzbBWMu2BXwMkzyCKcUjtEKPpgdZ7GEFKm/
+
+I couldn't figure out how to get a torrent client working on Google's VMs (perhaps a firewall issue), so I ended up using [aria2c]() to download the LLaMa weights from the IPFS mirror above.
+
+```
+apt-get install aria2
+
+mkdir -p $HOME/llama/13B
+cd $HOME/llama/13B
+aria2c https://ipfs.io/ipfs/QmPCfCEERStStjg4kfj3cmCUu1TP7pVQbxdFMwnhpuJtxk/consolidated.00.pth
+aria2c https://ipfs.io/ipfs/QmPCfCEERStStjg4kfj3cmCUu1TP7pVQbxdFMwnhpuJtxk/consolidated.01.pth
+aria2c https://ipfs.io/ipfs/QmPCfCEERStStjg4kfj3cmCUu1TP7pVQbxdFMwnhpuJtxk/checklist.chk
+aria2c https://ipfs.io/ipfs/QmPCfCEERStStjg4kfj3cmCUu1TP7pVQbxdFMwnhpuJtxk/params.json
+aria2c https://ipfs.io/ipfs/Qmb9y5GCkTG7ZzbBWMu2BXwMkzyCKcUjtEKPpgdZ7GEFKm/tokenizer.model
+```
+
+The `consolidated` files are the weights.
+`checklist.chk` has the md5 sums for the files, which you should check after they're downloaded.
+`params.json` seems to have some metadata.
+Finally, `tokenizer.model` is needed to convert the weights to HuggingFace format.
+
+## Convert weights to HuggingFace Format
+
+```
+pip install torch transformers accelerate sentencepiece protobuf==3.20
+python3 convert_llama_weights_to_hf.py --input_dir ~ --output_dir ~/llama-hf --model_size 13B
+```
+
+I used [rev d2ffc3fc4 of the script](https://github.com/huggingface/transformers/blob/d2ffc3fc48430f629c38c36fa8f308b045d1f715/src/transformers/models/llama/convert_llama_weights_to_hf.py).
+
+```
+apt-get install wget
+
+wget https://github.com/huggingface/transformers/blob/d2ffc3fc48430f629c38c36fa8f308b045d1f715/src/transformers/models/llama/convert_llama_weights_to_hf.py
+
+pip install torch transformers accelerate sentencepiece protobuf==3.20
+
+python3 convert_llama_weights_to_hf.py --input_dir $HOME/llama --output_dir $HOME/llama-hf --model_size 13B
+```
+
+These are the package versions that worked for me (note `protobuf=3.20` in the pip install command).
+
+| package        | version |
+|----------------|---------|
+|`torch`         | 2.0.0   |
+|`transformers`  | 4.28.1  |
+|`accelerate`    | 0.18.0  |
+|`sentencepiece` | 0.1.99  |
+|`protobuf`      | 3.20.0  |
+
+I got an error about regenerating protobuf functions if I used protobuf > 3.20.
+
+## Apply the vicuna deltas
+
+FastChat has done the work of getting a little chat interface set up.
+We'll use their package to download the deltas and apply them as well.
+
+```
+pip install fschat
+python3 -m fastchat.model.apply_delta \
+  --base-model-path $HOME/llama_hf \
+  --target-model-path $HOME/vicuna-13b \
+  --delta-path lmsys/vicuna-13b-delta-v1.1
+```
+
+I had `fschat 0.2.5`.
+
+## Start Chatting
+
+python3 -m fastchat.serve.cli --device cpu --model-path vicuna-13b/
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