Text Generation
Transformers
Safetensors
English
Hindi
Panjabi
language_model
multilingual
indic-languages
hindi
punjabi
small-model
Instructions to use PredictiveManish/Trimurti-LM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PredictiveManish/Trimurti-LM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="PredictiveManish/Trimurti-LM")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("PredictiveManish/Trimurti-LM", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use PredictiveManish/Trimurti-LM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "PredictiveManish/Trimurti-LM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PredictiveManish/Trimurti-LM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/PredictiveManish/Trimurti-LM
- SGLang
How to use PredictiveManish/Trimurti-LM 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 "PredictiveManish/Trimurti-LM" \ --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": "PredictiveManish/Trimurti-LM", "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 "PredictiveManish/Trimurti-LM" \ --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": "PredictiveManish/Trimurti-LM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use PredictiveManish/Trimurti-LM with Docker Model Runner:
docker model run hf.co/PredictiveManish/Trimurti-LM
Update README.md
Browse files
README.md
CHANGED
|
@@ -128,7 +128,7 @@ If you use Trimurti-LM in your work, please cite:
|
|
| 128 |
}
|
| 129 |
|
| 130 |
|
| 131 |
-
|
| 132 |
|
| 133 |
|
| 134 |
### Primary Dataset
|
|
@@ -141,4 +141,5 @@ If you use Trimurti-LM in your work, please cite:
|
|
| 141 |
year = {2021},
|
| 142 |
url = {https://arxiv.org/abs/2104.05596}
|
| 143 |
}
|
|
|
|
| 144 |
---
|
|
|
|
| 128 |
}
|
| 129 |
|
| 130 |
|
| 131 |
+
```
|
| 132 |
|
| 133 |
|
| 134 |
### Primary Dataset
|
|
|
|
| 141 |
year = {2021},
|
| 142 |
url = {https://arxiv.org/abs/2104.05596}
|
| 143 |
}
|
| 144 |
+
```
|
| 145 |
---
|