Instructions to use ianshank/phi-35-moe-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ianshank/phi-35-moe-instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ianshank/phi-35-moe-instruct", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ianshank/phi-35-moe-instruct", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("ianshank/phi-35-moe-instruct", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ianshank/phi-35-moe-instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ianshank/phi-35-moe-instruct" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ianshank/phi-35-moe-instruct", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ianshank/phi-35-moe-instruct
- SGLang
How to use ianshank/phi-35-moe-instruct 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 "ianshank/phi-35-moe-instruct" \ --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": "ianshank/phi-35-moe-instruct", "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 "ianshank/phi-35-moe-instruct" \ --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": "ianshank/phi-35-moe-instruct", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ianshank/phi-35-moe-instruct with Docker Model Runner:
docker model run hf.co/ianshank/phi-35-moe-instruct
| { | |
| "_name_or_path": "Phi-3.5-MoE-instruct", | |
| "architectures": [ | |
| "PhiMoEForCausalLM" | |
| ], | |
| "attention_bias": true, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_phimoe.PhiMoEConfig", | |
| "AutoModelForCausalLM": "modeling_phimoe.PhiMoEForCausalLM" | |
| }, | |
| "bos_token_id": 1, | |
| "eos_token_id": 32000, | |
| "hidden_act": "silu", | |
| "hidden_dropout": 0.0, | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "input_jitter_noise": 0.01, | |
| "intermediate_size": 6400, | |
| "lm_head_bias": true, | |
| "max_position_embeddings": 131072, | |
| "model_type": "phimoe", | |
| "num_attention_heads": 32, | |
| "num_experts_per_tok": 2, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "num_local_experts": 16, | |
| "original_max_position_embeddings": 4096, | |
| "output_router_logits": false, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "long_factor": [ | |
| 1.0199999809265137, | |
| 1.0299999713897705, | |
| 1.0399999618530273, | |
| 1.0499999523162842, | |
| 1.0499999523162842, | |
| 1.0499999523162842, | |
| 1.059999942779541, | |
| 1.059999942779541, | |
| 1.059999942779541, | |
| 1.059999942779541, | |
| 1.059999942779541, | |
| 1.059999942779541, | |
| 1.0999999046325684, | |
| 1.1799999475479126, | |
| 1.1799999475479126, | |
| 1.3700000047683716, | |
| 1.4899998903274536, | |
| 2.109999895095825, | |
| 2.8899998664855957, | |
| 3.9499998092651367, | |
| 4.299999713897705, | |
| 6.429999828338623, | |
| 8.09000015258789, | |
| 10.690000534057617, | |
| 12.050000190734863, | |
| 18.229999542236328, | |
| 18.84000015258789, | |
| 19.899999618530273, | |
| 21.420000076293945, | |
| 26.200000762939453, | |
| 34.28000259399414, | |
| 34.590003967285156, | |
| 38.730003356933594, | |
| 40.22000503540039, | |
| 42.54000473022461, | |
| 44.000003814697266, | |
| 47.590003967285156, | |
| 54.750003814697266, | |
| 56.19000244140625, | |
| 57.44000244140625, | |
| 57.4900016784668, | |
| 61.20000076293945, | |
| 61.540000915527344, | |
| 61.75, | |
| 61.779998779296875, | |
| 62.06999969482422, | |
| 63.11000061035156, | |
| 63.43000030517578, | |
| 63.560001373291016, | |
| 63.71000289916992, | |
| 63.92000198364258, | |
| 63.94000244140625, | |
| 63.94000244140625, | |
| 63.96000289916992, | |
| 63.980003356933594, | |
| 64.0300064086914, | |
| 64.0300064086914, | |
| 64.0300064086914, | |
| 64.04000854492188, | |
| 64.10000610351562, | |
| 64.19000244140625, | |
| 64.20999908447266, | |
| 64.75, | |
| 64.95999908447266 | |
| ], | |
| "long_mscale": 1.243163121016122, | |
| "original_max_position_embeddings": 4096, | |
| "short_factor": [ | |
| 1.0, | |
| 1.0399999618530273, | |
| 1.0399999618530273, | |
| 1.0399999618530273, | |
| 1.0499999523162842, | |
| 1.0499999523162842, | |
| 1.0499999523162842, | |
| 1.0499999523162842, | |
| 1.0499999523162842, | |
| 1.0499999523162842, | |
| 1.0499999523162842, | |
| 1.0499999523162842, | |
| 1.0499999523162842, | |
| 1.0499999523162842, | |
| 1.059999942779541, | |
| 1.059999942779541, | |
| 1.0699999332427979, | |
| 1.0699999332427979, | |
| 1.0699999332427979, | |
| 1.0699999332427979, | |
| 1.1399999856948853, | |
| 1.159999966621399, | |
| 1.159999966621399, | |
| 1.159999966621399, | |
| 1.159999966621399, | |
| 1.1799999475479126, | |
| 1.1999999284744263, | |
| 1.3199999332427979, | |
| 1.3399999141693115, | |
| 1.3499999046325684, | |
| 1.3999998569488525, | |
| 1.4799998998641968, | |
| 1.4999998807907104, | |
| 1.589999794960022, | |
| 1.6499998569488525, | |
| 1.71999990940094, | |
| 1.8999998569488525, | |
| 1.9099998474121094, | |
| 1.9099998474121094, | |
| 1.9899998903274536, | |
| 1.9999998807907104, | |
| 1.9999998807907104, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.009999990463257, | |
| 2.0999999046325684, | |
| 2.319999933242798, | |
| 2.419999837875366, | |
| 2.5899999141693115, | |
| 2.7899999618530273 | |
| ], | |
| "short_mscale": 1.243163121016122, | |
| "type": "longrope" | |
| }, | |
| "rope_theta": 10000.0, | |
| "router_aux_loss_coef": 0.0, | |
| "router_jitter_noise": 0.01, | |
| "sliding_window": 131072, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.43.3", | |
| "use_cache": true, | |
| "vocab_size": 32064 | |
| } | |