Instructions to use YtBig/href-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YtBig/href-v2 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="YtBig/href-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("YtBig/href-v2") model = AutoModelForSeq2SeqLM.from_pretrained("YtBig/href-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from YtBig/href-v2: direct link, hf CLI and curl.
- Browser
- Download file 671 Bytes
-
https://huggingface.co/YtBig/href-v2/resolve/main/README.md
- Command line
-
hf download hf://YtBig/href-v2/README.md
-
curl -L -o README.md https://huggingface.co/YtBig/href-v2/resolve/main/README.md
671 Bytes
| tags: | |
| - autotrain | |
| - summarization | |
| language: | |
| - en | |
| widget: | |
| - text: "I love AutoTrain 🤗" | |
| co2_eq_emissions: | |
| emissions: 2295.967887402507 | |
| # Model Trained Using AutoTrain | |
| - Problem type: Summarization | |
| - Model ID: 2346773844 | |
| - CO2 Emissions (in grams): 2295.9679 | |
| ## Validation Metrics | |
| - Loss: 2.208 | |
| - Rouge1: 26.910 | |
| - Rouge2: 14.562 | |
| - RougeL: 24.804 | |
| - RougeLsum: 25.155 | |
| - Gen Len: 19.930 | |
| ## Usage | |
| You can use cURL to access this model: | |
| ``` | |
| $ curl -X POST -H "Authorization: Bearer YOUR_HUGGINGFACE_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/Alfred-o/autotrain-tag-href-2346773844 | |
| ``` |