Text Classification
Transformers
Safetensors
English
decision-model
decision-index
system-one
gemma4
qwen3_5
Instructions to use Poindexter-Labs/Copernicus-57B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Poindexter-Labs/Copernicus-57B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Poindexter-Labs/Copernicus-57B")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Poindexter-Labs/Copernicus-57B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download engine/Dockerfile.conv from Poindexter-Labs/Copernicus-57B: direct link, hf CLI and curl.
- Browser
- Download file 471 Bytes
-
https://huggingface.co/Poindexter-Labs/Copernicus-57B/resolve/main/engine/Dockerfile.conv
- Command line
-
hf download hf://Poindexter-Labs/Copernicus-57B/engine/Dockerfile.conv
-
curl -L -o Dockerfile.conv https://huggingface.co/Poindexter-Labs/Copernicus-57B/resolve/main/engine/Dockerfile.conv
471 Bytes
| FROM reax13-base | |
| RUN pip install --no-cache-dir 'ninja==1.13.2' 'nvidia-cuda-cccl==13.0.85' | |
| RUN CAUSAL_CONV1D_FORCE_BUILD=TRUE MAX_JOBS=4 CUDA_HOME=/usr/local/cuda TORCH_CUDA_ARCH_LIST=12.0 pip install --no-cache-dir --no-build-isolation --no-deps 'causal-conv1d==1.7.0' | |
| RUN python -c 'import causal_conv1d, torch; print(causal_conv1d.__version__, torch.__version__)' | |
| RUN pip install --no-cache-dir 'httpx==0.28.1' | |
| COPY . /engine | |
| ENV PYTHONPATH=/engine | |
| WORKDIR /engine | |