Text Generation
Transformers
ONNX
Transformers.js
lfm2
emoji
thinking
chain-of-thought
pantheon
unsloth
lfm
webgpu
conversational
Instructions to use shreyask/pantheon-ui-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shreyask/pantheon-ui-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="shreyask/pantheon-ui-onnx") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("shreyask/pantheon-ui-onnx") model = AutoModelForCausalLM.from_pretrained("shreyask/pantheon-ui-onnx", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Transformers.js
How to use shreyask/pantheon-ui-onnx with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-generation', 'shreyask/pantheon-ui-onnx'); - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use shreyask/pantheon-ui-onnx with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "shreyask/pantheon-ui-onnx" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "shreyask/pantheon-ui-onnx", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/shreyask/pantheon-ui-onnx
- SGLang
How to use shreyask/pantheon-ui-onnx 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 "shreyask/pantheon-ui-onnx" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "shreyask/pantheon-ui-onnx", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "shreyask/pantheon-ui-onnx" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "shreyask/pantheon-ui-onnx", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Desktop
- Docker Model Runner
How to use shreyask/pantheon-ui-onnx with Docker Model Runner:
docker model run hf.co/shreyask/pantheon-ui-onnx
Commit History
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Update model card with correct attributions
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fix: set kv_cache_dtype q4->float16 and torch_dtype float16
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fix: add tokenizer_config with chat_template from base model
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add model_q4.onnx_data
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add model_q4.onnx with correct external data ref
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fix: config with q4 dtype mapping
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int4 WebGPU ONNX with patched external data refs
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cleanup: remove fp16 files
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fix: use full model config from merged model
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fix: add fp16 dtype mapping to transformers.js_config
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fp16 WebGPU ONNX (no quantization, compatible ops)
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cleanup: remove old/duplicate ONNX files
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fix: patch external data refs to underscore format (model.onnx_data)
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fix: keep original ONNX filenames to match internal data references
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v3: WebGPU int4 ONNX from 6-epoch fine-tune (loss 1.059)
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Add generation_config.json
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Restructure ONNX for Transformers.js compatibility (onnx/ subdir + config)
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Add model card
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Upload ONNX int4 model via Xenova's LFM2 builder
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initial commit
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