Instructions to use SaadRa/test_deepseek_hf_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaadRa/test_deepseek_hf_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SaadRa/test_deepseek_hf_model", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SaadRa/test_deepseek_hf_model", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download generation_config.json from SaadRa/test_deepseek_hf_model: direct link, hf CLI and curl.
- Browser
- Download file 154 Bytes
-
https://huggingface.co/SaadRa/test_deepseek_hf_model/resolve/main/generation_config.json
- Command line
-
hf download hf://SaadRa/test_deepseek_hf_model/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/SaadRa/test_deepseek_hf_model/resolve/main/generation_config.json
154 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 0, | |
| "eos_token_id": 1, | |
| "max_length": 8192, | |
| "pad_token_id": 2, | |
| "transformers_version": "4.56.2" | |
| } | |