Instructions to use Chaitanya182004/nl2sql-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chaitanya182004/nl2sql-model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Chaitanya182004/nl2sql-model") model = AutoModelForSeq2SeqLM.from_pretrained("Chaitanya182004/nl2sql-model") - Notebooks
- Google Colab
- Kaggle
| {% if not add_generation_prompt is defined %} | |
| {% set add_generation_prompt = false %} | |
| {% endif %} | |
| {%- set ns = namespace(found=false) -%} | |
| {%- for message in messages -%} | |
| {%- if message['role'] == 'system' -%} | |
| {%- set ns.found = true -%} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {{bos_token}}{%- if not ns.found -%} | |
| {{'You are an AI programming assistant, utilizing the Deepseek Coder model, developed by Deepseek Company, and you only answer questions related to computer science. For politically sensitive questions, security and privacy issues, and other non-computer science questions, you will refuse to answer\n'}} | |
| {%- endif %} | |
| {%- for message in messages %} | |
| {%- if message['role'] == 'system' %} | |
| {{ message['content'] }} | |
| {%- else %} | |
| {%- if message['role'] == 'user' %} | |
| {{'### Instruction:\n' + message['content'] + '\n'}} | |
| {%- else %} | |
| {{'### Response:\n' + message['content'] + '\n<|EOT|>\n'}} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {% if add_generation_prompt %} | |
| {{'### Response:'}} | |
| {% endif %} |