Instructions to use stockmark/stockmark-100b-instruct-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stockmark/stockmark-100b-instruct-v0.1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("stockmark/stockmark-100b-instruct-v0.1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
You should add a chat_template to the tokenizer_config?
#1
by leonardlin - opened
This should work for your JA Alpaca format:
{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'].strip() + '\n\n' %}{% else %}{% set loop_messages = messages %}{% set system_message = '' %}{% endif %}{{ bos_token + system_message }}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '### 指示:\n' + message['content'].strip() + '\n\n' }}{% elif message['role'] == 'assistant' %}{{ '### 応答:\n' + message['content'].strip() + eos_token + '\n\n' }}{% endif %}{% if loop.last and message['role'] == 'user' and add_generation_prompt %}{{ '### 指示:\n' }}{% endif %}{% endfor %}