I am trying to run DeepSeek locally according to their instructions but it does not work with some silly error (I will show it later). This is what I am doing.

1. Download the smallest model (3.5GB) from here .5B
2. Follow the steps from here: #6-how-to-run-locally

2.1 Get this project .git

2.2 Run docker container like this with pre-created volume to put the model

docker run --gpus all -it --name deepseek01 --rm --mount source=deepseekv3,target=/root/deepseekv3 python:3.10-slim bash

I am using python:3.10-slim because here (#6-how-to-run-locally) it is written "Linux with Python 3.10 only. Mac and Windows are not supported."

2.3 Install latest updates apt-get update

2.4 get this file .txt and install the requirements

pip install -r requirements.txt

2.5 Copy the model to the volume mounted to the docker container. these 5 files from here .5B

config.json
generation_config.json
model.safetensors
tokenizer.json
tokenizer_config.json

2.6 Convert the model as it is written here #model-weights-conversion by this command

python convert.py --hf-ckpt-path /root/deepseekv3/source_model --save-path /root/deepseekv3/converted_model --n-experts 256 --model-parallel 16

In this step (converting the model) I got this error

Traceback (most recent call last):
  File "/root/deepseekv3/inference/convert.py", line 96, in <module>
    main(args.hf_ckpt_path, args.save_path, args.n_experts, args.model_parallel)
  File "/root/deepseekv3/inference/convert.py", line 63, in main
    assert key in mapping
AssertionError

so, basically, the next steps do not make sense, as this is the essential step.

My questions:

1. What I am doing wrong?
2. There are some videos on YouTube where deepseek was installed with ollama. Is it really required? Should I be able to run it without it like they described here #6-how-to-run-locally?

UPDATE 1

In order to debug a bit I added these 2 lines.

print("Missing key:", key)
print("Available keys:", list(mapping.keys()))

Missing keys were identified as these:

embed_tokens
input_layernorm
down_proj
gate_proj
up_proj
post_attention_layernorm
k_proj

Although all of them do exist inside model.safetensors file.

Also, it was mentioned by @Hans Kilian in the comment, that I might put some file, which is not needed into source_model folder. I checked line 11 in the convert.py and some of the keys there do not exist inside model.safetensors, but logging reports different keys.