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)# 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=40) 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 Studio
How to use shreyask/pantheon-ui-onnx with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for shreyask/pantheon-ui-onnx to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for shreyask/pantheon-ui-onnx to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for shreyask/pantheon-ui-onnx to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="shreyask/pantheon-ui-onnx", max_seq_length=2048, ) - Docker Model Runner
How to use shreyask/pantheon-ui-onnx with Docker Model Runner:
docker model run hf.co/shreyask/pantheon-ui-onnx
fp16 WebGPU ONNX (no quantization, compatible ops)
Browse files- generation_config.json +1 -2
- onnx/model.onnx +2 -2
- onnx/model.onnx_data +2 -2
generation_config.json
CHANGED
|
@@ -2,6 +2,5 @@
|
|
| 2 |
"_from_model_config": true,
|
| 3 |
"bos_token_id": 1,
|
| 4 |
"eos_token_id": 7,
|
| 5 |
-
"pad_token_id": 0
|
| 6 |
-
"transformers_version": "5.1.0"
|
| 7 |
}
|
|
|
|
| 2 |
"_from_model_config": true,
|
| 3 |
"bos_token_id": 1,
|
| 4 |
"eos_token_id": 7,
|
| 5 |
+
"pad_token_id": 0
|
|
|
|
| 6 |
}
|
onnx/model.onnx
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:292bad950fe2cddf413b119d71e6972eb84c1da9b5805b5560ef55700d46fbd0
|
| 3 |
+
size 138095
|
onnx/model.onnx_data
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e85523d5c8c5a57a4282fa24f69baee6aae1ae2c2087960b7bc3858fc192a420
|
| 3 |
+
size 2357067776
|