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Updated Templates supported by llama_chat_apply_template (markdown)
kaizau
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@ -6,50 +6,6 @@ This is the list of templates currently supported by `llama_apply_chat_template`
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## Supported templates
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<details>
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<summary>Python code</summary>
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```python
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from transformers import AutoTokenizer
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VARIANTS_TO_TEST = [
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'teknium/OpenHermes-2.5-Mistral-7B',
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'mistralai/Mistral-7B-Instruct-v0.2',
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'TheBloke/FusionNet_34Bx2_MoE-AWQ',
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'bofenghuang/vigogne-2-70b-chat',
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'mlabonne/AlphaMonarch-7B',
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'google/gemma-7b-it',
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'OrionStarAI/Orion-14B-Chat',
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'openbmb/MiniCPM-2B-dpo-fp32',
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]
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HISTORY = [
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{ 'role': 'system', 'content': 'test' },
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{ 'role': 'user', 'content': 'hello' },
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{ 'role': 'assistant', 'content': 'response' },
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{ 'role': 'user', 'content': 'again' },
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{ 'role': 'assistant', 'content': 'response' },
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]
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for variant in VARIANTS_TO_TEST:
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history = [m for m in HISTORY] # copy
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if 'Mistral' in variant or 'gemma' in variant:
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history.pop(0) # no system prompt for mistral and gemma
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if 'gemma' in variant:
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# GemmaTokenizer is quite buggy, let's hard code the template here
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GEMMA_TMLP = "{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}"
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print('Gemma')
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output = AutoTokenizer.from_pretrained(VARIANTS_TO_TEST[0]).apply_chat_template(history, tokenize=False, chat_template=GEMMA_TMLP)
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print(output)
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print('-' * 30)
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else:
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print(variant)
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tokenizer = AutoTokenizer.from_pretrained(variant)
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print(tokenizer.apply_chat_template(history, tokenize=False))
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print('-' * 30)
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```
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</details>
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```
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Usage: ./server -m ... --chat-template chatml
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teknium/OpenHermes-2.5-Mistral-7B
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@ -126,22 +82,6 @@ Assistant: </s>response</s>Human: again
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Assistant: </s>response</s>
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```
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Additionally, we also support zephyr template (I cannot find it on huggingface, but have seen in [this list](https://github.com/ggerganov/llama.cpp/blob/c8d847d57efdc0f9bbbf881d48c645e151b36fd8/examples/server/public/promptFormats.js) )
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```
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Usage: ./server -m ... --chat-template zephyr
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<|system|>
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test<|endoftext|>
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<|user|>
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hello<|endoftext|>
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<|assistant|>
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response<|endoftext|>
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<|user|>
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again<|endoftext|>
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<|assistant|>
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response<|endoftext|>
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```
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```
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Usage: ./server -m ... --chat-template openchat
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openchat/openchat-3.5-0106
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@ -192,6 +132,88 @@ Another question
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```
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Additionally, we also support zephyr template (I cannot find it on huggingface, but have seen in [this list](https://github.com/ggerganov/llama.cpp/blob/c8d847d57efdc0f9bbbf881d48c645e151b36fd8/examples/server/public/promptFormats.js) )
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```
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Usage: ./server -m ... --chat-template zephyr
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<|system|>
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test<|endoftext|>
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<|user|>
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hello<|endoftext|>
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<|assistant|>
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response<|endoftext|>
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<|user|>
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again<|endoftext|>
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<|assistant|>
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response<|endoftext|>
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```
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## How to add a new template
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1. Check the `chat_template` in the model's HuggingFace `tokenizer_config.json` [(example)](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2/blob/main/tokenizer_config.json#L42).
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- If there isn't one, open an issue first to discuss. Some older models actually predate chat templates and multi-turn responses and would be difficult to support.
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2. Use the following python script to generate a test conversation.
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<details>
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<summary>Script</summary>
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```python
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from transformers import AutoTokenizer
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VARIANTS_TO_TEST = [
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'teknium/OpenHermes-2.5-Mistral-7B',
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'mistralai/Mistral-7B-Instruct-v0.2',
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'TheBloke/FusionNet_34Bx2_MoE-AWQ',
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'bofenghuang/vigogne-2-70b-chat',
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'mlabonne/AlphaMonarch-7B',
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'google/gemma-7b-it',
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'OrionStarAI/Orion-14B-Chat',
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'openbmb/MiniCPM-2B-dpo-fp32',
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'openchat/openchat-3.5-0106',
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'deepseek-ai/deepseek-coder-33b-instruct',
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# Replace with your model's HuggingFace name
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]
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HISTORY = [
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{ 'role': 'system', 'content': 'You are a helpful assistant' },
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{ 'role': 'user', 'content': 'Hello' },
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{ 'role': 'assistant', 'content': 'Hi there' },
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{ 'role': 'user', 'content': 'Who are you' },
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{ 'role': 'assistant', 'content': ' I am an assistant ' },
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{ 'role': 'user', 'content': 'Another question' },
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]
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for variant in VARIANTS_TO_TEST:
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history = [m for m in HISTORY] # copy
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if 'Mistral' in variant or 'gemma' in variant:
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history.pop(0) # no system prompt for mistral and gemma
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if 'gemma' in variant:
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# GemmaTokenizer is quite buggy, let's hard code the template here
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GEMMA_TMLP = "{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}"
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print("\n----- Gemma -----")
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output = AutoTokenizer.from_pretrained(VARIANTS_TO_TEST[0]).apply_chat_template(history, tokenize=False, add_generation_prompt=True, chat_template=GEMMA_TMLP)
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print(output)
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print("\n[Test String]\n// google/gemma-7b-it")
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print(output.replace("\n", "\\n"))
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print('"' + output.replace("\n", "\\n") + '",')
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else:
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print("\n----- " + variant + " -----")
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tokenizer = AutoTokenizer.from_pretrained(variant)
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output = tokenizer.apply_chat_template(history, tokenize=False, add_generation_prompt=True)
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print(output)
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print("\n[Test String]\n// " + variant)
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print('"' + output.replace("\n", "\\n") + '",')
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```
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</details>
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3. Copy both the `chat_template` from HuggingFace and the formatted text below `[Test String]` into [tests/test-chat-template.cpp](https://github.com/ggerganov/llama.cpp/blob/master/tests/test-chat-template.cpp).
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4. Run `make tests/test-chat-template`. You can now use this test to verify that your template implementation is identical to the original.
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5. Implement your template in llama.cpp (search for `llama_chat_apply_template_internal`).
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- This function attempts to detect the model's template when it's not specified. This uses the model's `chat_template` metadata, so pick a unique pattern.
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6. `make` and run the test. Repeat until the output matches the original!
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## Custom chat templates
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Currently, it's not possible to use your own chat template with llama.cpp server's `/chat/completions`
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