Feature Extraction
Transformers
PyTorch
qwen3
llama-factory
full
Generated from Trainer
custom_code
text-embeddings-inference
Instructions to use Time-HD-Anonymous/STReasoner-8B-CoT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Time-HD-Anonymous/STReasoner-8B-CoT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Time-HD-Anonymous/STReasoner-8B-CoT", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Time-HD-Anonymous/STReasoner-8B-CoT", trust_remote_code=True) model = AutoModel.from_pretrained("Time-HD-Anonymous/STReasoner-8B-CoT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Time-HD-Anonymous/STReasoner-8B-CoT: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Time-HD-Anonymous/STReasoner-8B-CoT/resolve/main/tokenizer.json
- Command line
-
hf download hf://Time-HD-Anonymous/STReasoner-8B-CoT/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Time-HD-Anonymous/STReasoner-8B-CoT/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 4bdf2fe396e9a71d8f29b528425c138e6140666ce183fcfce04f3e942e486570
- Size of remote file:
- 11.4 MB
- SHA256:
- f58249c804f02dc95986d90822c6ca889b91cfdd40befa5066ff7d50fce80342
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