Text Classification
Transformers
Safetensors
internlm2
text-generation
hallucination-detection
custom_code
Instructions to use opencompass/anah-20b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opencompass/anah-20b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="opencompass/anah-20b", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("opencompass/anah-20b", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add missing metadata: `pipeline_tag`, `library_name`, and `license`
#1
by nielsr HF Staff - opened
This PR adds the missing pipeline_tag, library_name, and license to the model card metadata. The pipeline_tag is set to text-classification, which reflects the model's function of classifying text segments as hallucinations or not. The license is retrieved from the Github page. This improved metadata enhances the model's discoverability and provides essential information for users.
vanilla1116 changed pull request status to merged