Instructions to use impactframes/IF-PromptMKR-phi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use impactframes/IF-PromptMKR-phi with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="impactframes/IF-PromptMKR-phi", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("impactframes/IF-PromptMKR-phi", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use impactframes/IF-PromptMKR-phi with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "impactframes/IF-PromptMKR-phi"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "impactframes/IF-PromptMKR-phi",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/impactframes/IF-PromptMKR-phi

SGLang

How to use impactframes/IF-PromptMKR-phi 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 "impactframes/IF-PromptMKR-phi" \
    --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": "impactframes/IF-PromptMKR-phi",
		"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 "impactframes/IF-PromptMKR-phi" \
        --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": "impactframes/IF-PromptMKR-phi",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use impactframes/IF-PromptMKR-phi with Docker Model Runner:
```
docker model run hf.co/impactframes/IF-PromptMKR-phi
```

IF-PromptMKR-phi

File size: 707 Bytes

37cc5cf

{
  "_name_or_path": "phi-1.5-half",
  "activation_function": "gelu_new",
  "architectures": [
    "MixFormerSequentialForCausalLM"
  ],
  "auto_map": {
    "AutoConfig": "configuration_mixformer_sequential.MixFormerSequentialConfig",
    "AutoModelForCausalLM": "modeling_mixformer_sequential.MixFormerSequentialForCausalLM"
  },
  "embd_pdrop": 0.0,
  "initializer_range": 0.02,
  "layer_norm_epsilon": 1e-05,
  "model_type": "mixformer-sequential",
  "n_embd": 2048,
  "n_head": 32,
  "n_inner": null,
  "n_layer": 24,
  "n_positions": 2048,
  "resid_pdrop": 0.0,
  "rotary_dim": 32,
  "tie_word_embeddings": false,
  "torch_dtype": "float16",
  "transformers_version": "4.32.1",
  "vocab_size": 51200
}