Summarization
PEFT
Safetensors
fake news detection
propaganda
fake news
propaganda detection
manipulative constructions analysis
offensive language analysis
text-generation
Instructions to use bpavlsh/Mistral-Fake-News-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bpavlsh/Mistral-Fake-News-Detection with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") model = PeftModel.from_pretrained(base_model, "bpavlsh/Mistral-Fake-News-Detection") - Notebooks
- Google Colab
- Kaggle
| {%- if messages[0]['role'] == 'system' %} | |
| {%- set system_message = messages[0]['content'] %} | |
| {%- set loop_messages = messages[1:] %} | |
| {%- else %} | |
| {%- set loop_messages = messages %} | |
| {%- endif %} | |
| {{- bos_token }} | |
| {%- for message in loop_messages %} | |
| {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) %} | |
| {{- raise_exception('After the optional system message, conversation roles must alternate user/assistant/user/assistant/...') }} | |
| {%- endif %} | |
| {%- if message['role'] == 'user' %} | |
| {%- if loop.first and system_message is defined %} | |
| {{- ' [INST] ' + system_message + '\n\n' + message['content'] + ' [/INST]' }} | |
| {%- else %} | |
| {{- ' [INST] ' + message['content'] + ' [/INST]' }} | |
| {%- endif %} | |
| {%- elif message['role'] == 'assistant' %} | |
| {{- ' ' + message['content'] + eos_token}} | |
| {%- else %} | |
| {{- raise_exception('Only user and assistant roles are supported, with the exception of an initial optional system message!') }} | |
| {%- endif %} | |
| {%- endfor %} | |