Instructions to use rxmha125/Rx_Codex_Tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rxmha125/Rx_Codex_Tokenizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="rxmha125/Rx_Codex_Tokenizer")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rxmha125/Rx_Codex_Tokenizer", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use rxmha125/Rx_Codex_Tokenizer with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rxmha125/Rx_Codex_Tokenizer" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rxmha125/Rx_Codex_Tokenizer", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/rxmha125/Rx_Codex_Tokenizer
- SGLang
How to use rxmha125/Rx_Codex_Tokenizer 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 "rxmha125/Rx_Codex_Tokenizer" \ --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": "rxmha125/Rx_Codex_Tokenizer", "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 "rxmha125/Rx_Codex_Tokenizer" \ --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": "rxmha125/Rx_Codex_Tokenizer", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use rxmha125/Rx_Codex_Tokenizer with Docker Model Runner:
docker model run hf.co/rxmha125/Rx_Codex_Tokenizer
Upload compression_comparison.png with huggingface_hub
Browse files- .gitattributes +1 -0
- compression_comparison.png +3 -0
.gitattributes
CHANGED
|
@@ -35,3 +35,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
performance_breakdown.png filter=lfs diff=lfs merge=lfs -text
|
| 37 |
speed_comparison.png filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
performance_breakdown.png filter=lfs diff=lfs merge=lfs -text
|
| 37 |
speed_comparison.png filter=lfs diff=lfs merge=lfs -text
|
| 38 |
+
compression_comparison.png filter=lfs diff=lfs merge=lfs -text
|
compression_comparison.png
ADDED
|
Git LFS Details
|