Configuration confusion
I am confused about the correct EOS/BOS.
In generation_config.json and config.json the settings differ:
latter:
{
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"bos_token_id": 1,
"eos_token_id": 2,
"hidden_act": "silu",
"hidden_size": 7168,
"initializer_range": 0.02,
"intermediate_size": 20480,
"max_position_embeddings": 4096,
"model_type": "llama",
"num_attention_heads": 56,
"num_hidden_layers": 60,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 5000000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.35.0",
"use_cache": true,
"vocab_size": 64000
}
former:
{
"bos_token_id": 6,
"do_sample": true,
"eos_token_id": 7,
"pad_token_id": 0,
"temperature": 0.6,
"max_length": 4096,
"top_p": 0.8,
"transformers_version": "4.35.0"
}
If I understand https://github.com/huggingface/transformers/issues/25395#issuecomment-1677796723 correctly, it's a fallback mechanism.
That would give
"bos_token_id": 6,
"eos_token_id": 7,
However, maybe they are not added at all, as in tokenizer_config.json we have:
{
"add_bos_token": false,
"add_eos_token": false,
"added_tokens_decoder": {
"0": {
"content": "<unk>",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false,
"special": true
},
"1": {
"content": "<|startoftext|>",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false,
"special": true
},
"2": {
"content": "<|endoftext|>",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false,
"special": true
},
"6": {
"content": "<|im_start|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"7": {
"content": "<|im_end|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"8": {
"content": "<|im_sep|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"additional_special_tokens": [
"<|im_start|>",
"<|im_end|>",
"<|im_sep|>"
],
"bos_token": "<|startoftext|>",
"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
"clean_up_tokenization_spaces": false,
"eos_token": "<|endoftext|>",
"legacy": true,
"model_max_length": 4096,
"pad_token": "<unk>",
"padding_side": "right",
"sp_model_kwargs": {},
"spaces_between_special_tokens": false,
"tokenizer_class": "LlamaTokenizer",
"unk_token": "<unk>",
"use_default_system_prompt": true
}
note the:
"add_bos_token": false,
"add_eos_token": false,
And thus, why are bos_token and eos_token still specified here?
Hi @krao
The generate function will use eos token as stop token. In our chat template format(which is ChatML), we use the "<|im_end|>" as the end token of the response. So we change the eos_token_id in generation_config to 7 which map to "<|im_end|>".
And yes, the bos_token_id should have no effect here.
And yes, the bos_token_id should have no effect here.
Do you mean bos_token and eos_token?
reedcliThe chat model is developed upon the base model, which utilizes distinct training templates:
- base model: Typically trained with a template such as "{document}<|endoftext|>", To format this appropriately, one can employ
tokenizer.encode(document, add_bos_token=add_bos_token, add_eos_token=add_eos_token), and designate "<|endoftext|>" as the stop token during generation. - chat model: Often trained using a template represented by "<|im_start|>...<|im_end|>", For proper formatting, the method
tokenizer.apply_chat_template(messages)is used, and designate "<|im_end|>" as stop token during generation.
It's important to note that the bos and eos settings found in config.json and tokenizer_config.json are inherited from the base model. However, the settings in generation_config.json are specifically defined by the chat model.
If you have any further question, feel free to ask!
Thank you, that was really helpful!
Hi, can I just modify the bos and eos setting in config.json and tokenizer_config.json and make it align with generation_config.json? If yes, I can make a PR.