Summarization
Transformers
PyTorch
Safetensors
English
Portuguese
mt5
text2text-generation
Eval Results (legacy)
Instructions to use cloudqi/cqi_brain_memory_summarizer_large_pt_v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cloudqi/cqi_brain_memory_summarizer_large_pt_v0 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="cloudqi/cqi_brain_memory_summarizer_large_pt_v0")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cloudqi/cqi_brain_memory_summarizer_large_pt_v0") model = AutoModelForSeq2SeqLM.from_pretrained("cloudqi/cqi_brain_memory_summarizer_large_pt_v0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from cloudqi/cqi_brain_memory_summarizer_large_pt_v0: direct link, hf CLI and curl.
- Browser
- Download file 1.36 MB
-
https://huggingface.co/cloudqi/cqi_brain_memory_summarizer_large_pt_v0/resolve/main/tokenizer.json
- Command line
-
hf download hf://cloudqi/cqi_brain_memory_summarizer_large_pt_v0/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/cloudqi/cqi_brain_memory_summarizer_large_pt_v0/resolve/main/tokenizer.json
1.36 MB
File too large to display, you can check the raw version instead.