Mistral.rs attempts to automatically load a chat template from the tokenizer_config.json
file. This enables high flexibility across instruction-tuned models and ensures accurate chat templating. However, if the chat_template
field is missing, then a JINJA chat template should be provided. The JINJA chat template may use messages
, add_generation_prompt
, bos_token
, eos_token
, and unk_token
as inputs. Some chat templates are provided here, and it is easy to modify or create others.
For example, to use the chatml
template, --chat-template
is specified before the model architecture. For example:
./mitralrs-server --port 1234 --log output.log --chat-template ./chat_templates/chatml.json llama
Some models do not provide a tokenizer.json
file although mistral.rs expects one. To solve this, please run this script. It will output the tokenizer.json
file for your specific model. This may be used by passing the --tokenizer-json
flag after the model architecture. For example:
$ python3 scripts/get_tokenizers_json.py
Enter model ID: microsoft/Orca-2-13b
$ ./mistralrs_server --port 1234 --log output.log plain -m microsoft/Orca-2-13b --tokenizer-json tokenizer.json
Putting it all together, to run, for example, an Orca model (which does not come with a tokenizer.json
or chat template):
- Generate the
tokenizer.json
by running the script atscripts/get_tokenizers_json.py
. This will output some files includingtokenizer.json
in the working directory. - Find and copy the correct chat template from
chat-templates
to the working directory (eg.,cp chat_templates/chatml.json .
) - Run
mistralrs-server
, specifying the tokenizer and chat template:cargo run --release --features cuda -- --port 1234 --log output.txt --chat-template chatml.json plain -m microsoft/Orca-2-13b -t tokenizer.json -a llama