Text Generation
Transformers
Safetensors
Chinese
reinforcement-learning
grpo
adaptive-rubric
script-generation
Instructions to use EurekaTian/RARE-Task-Level with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EurekaTian/RARE-Task-Level with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="EurekaTian/RARE-Task-Level")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("EurekaTian/RARE-Task-Level", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use EurekaTian/RARE-Task-Level with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "EurekaTian/RARE-Task-Level" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EurekaTian/RARE-Task-Level", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/EurekaTian/RARE-Task-Level
- SGLang
How to use EurekaTian/RARE-Task-Level with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "EurekaTian/RARE-Task-Level" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EurekaTian/RARE-Task-Level", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "EurekaTian/RARE-Task-Level" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EurekaTian/RARE-Task-Level", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use EurekaTian/RARE-Task-Level with Docker Model Runner:
docker model run hf.co/EurekaTian/RARE-Task-Level
Download 2d_animation/tokenizer.json from EurekaTian/RARE-Task-Level: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/EurekaTian/RARE-Task-Level/resolve/main/2d_animation/tokenizer.json
- Command line
-
hf download hf://EurekaTian/RARE-Task-Level/2d_animation/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/EurekaTian/RARE-Task-Level/resolve/main/2d_animation/tokenizer.json
11.4 MB
- Xet hash:
- 693ec4b3922b0bd306bf7b4989e115ffbfeb7b0c08b31bc6d956818c6bb07f61
- Size of remote file:
- 11.4 MB
- SHA256:
- aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
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