Instructions to use jerryzh168/phi4-float8dq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jerryzh168/phi4-float8dq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jerryzh168/phi4-float8dq") 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("jerryzh168/phi4-float8dq") model = AutoModelForCausalLM.from_pretrained("jerryzh168/phi4-float8dq", 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]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use jerryzh168/phi4-float8dq with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jerryzh168/phi4-float8dq" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jerryzh168/phi4-float8dq", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/jerryzh168/phi4-float8dq
- SGLang
How to use jerryzh168/phi4-float8dq 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 "jerryzh168/phi4-float8dq" \ --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": "jerryzh168/phi4-float8dq", "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 "jerryzh168/phi4-float8dq" \ --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": "jerryzh168/phi4-float8dq", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use jerryzh168/phi4-float8dq with Docker Model Runner:
docker model run hf.co/jerryzh168/phi4-float8dq
Download config.json from jerryzh168/phi4-float8dq: direct link, hf CLI and curl.
- Browser
- Download file 1.74 kB
-
https://huggingface.co/jerryzh168/phi4-float8dq/resolve/main/config.json
- Command line
-
hf download hf://jerryzh168/phi4-float8dq/config.json
-
curl -L -o config.json https://huggingface.co/jerryzh168/phi4-float8dq/resolve/main/config.json
1.74 kB
| { | |
| "architectures": [ | |
| "Phi3ForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 100257, | |
| "embd_pdrop": 0.0, | |
| "eos_token_id": 100265, | |
| "hidden_act": "silu", | |
| "hidden_size": 5120, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 17920, | |
| "max_position_embeddings": 16384, | |
| "model_type": "phi3", | |
| "num_attention_heads": 40, | |
| "num_hidden_layers": 40, | |
| "num_key_value_heads": 10, | |
| "original_max_position_embeddings": 16384, | |
| "pad_token_id": 100349, | |
| "partial_rotary_factor": 1.0, | |
| "quantization_config": { | |
| "modules_to_not_convert": null, | |
| "quant_method": "torchao", | |
| "quant_type": { | |
| "default": { | |
| "_data": { | |
| "activation_dtype": { | |
| "_data": "float8_e4m3fn", | |
| "_type": "torch.dtype" | |
| }, | |
| "granularity": { | |
| "_data": {}, | |
| "_type": "PerRow", | |
| "_version": 1 | |
| }, | |
| "mm_config": { | |
| "_data": { | |
| "emulate": false, | |
| "pad_inner_dim": false, | |
| "use_fast_accum": true | |
| }, | |
| "_type": "Float8MMConfig", | |
| "_version": 1 | |
| }, | |
| "set_inductor_config": true, | |
| "weight_dtype": { | |
| "_data": "float8_e4m3fn", | |
| "_type": "torch.dtype" | |
| } | |
| }, | |
| "_type": "Float8DynamicActivationFloat8WeightConfig", | |
| "_version": 1 | |
| } | |
| }, | |
| "quant_type_kwargs": {} | |
| }, | |
| "resid_pdrop": 0.0, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "rope_theta": 250000, | |
| "sliding_window": null, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.51.0.dev0", | |
| "use_cache": true, | |
| "vocab_size": 100352 | |
| } | |