Instructions to use AIuser2222/Cyn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use AIuser2222/Cyn with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("AIuser2222/Cyn", set_active=True) - Notebooks
- Google Colab
- Kaggle
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Download README.md from AIuser2222/Cyn: direct link, hf CLI and curl.
- Browser
- Download file 729 Bytes
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https://huggingface.co/AIuser2222/Cyn/resolve/main/README.md
- Command line
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hf download hf://AIuser2222/Cyn/README.md
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curl -L -o README.md https://huggingface.co/AIuser2222/Cyn/resolve/main/README.md
729 Bytes
metadata
license: apache-2.0
datasets:
- HuggingFaceTB/everyday-conversations-llama3.1-2k
base_model: mattshumer/Reflection-Llama-3.1-70B
library_name: adapter-transformers
My AI Model
Model Description
This model is designed for [task description] using [dataset name]. It has been fine-tuned to achieve [performance metrics].
Usage
You can use the model with the following code:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("username/model_name")
model = AutoModelForSequenceClassification.from_pretrained("username/model_name")
inputs = tokenizer("Hello, Hugging Face!", return_tensors="pt")
outputs = model(**inputs)
print(outputs)