Instructions to use BucketOfFish/simplified_phi2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use BucketOfFish/simplified_phi2 with Transformers:

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

pipe = pipeline("text-generation", model="BucketOfFish/simplified_phi2", trust_remote_code=True)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("BucketOfFish/simplified_phi2", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use BucketOfFish/simplified_phi2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "BucketOfFish/simplified_phi2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BucketOfFish/simplified_phi2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/BucketOfFish/simplified_phi2

SGLang

How to use BucketOfFish/simplified_phi2 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 "BucketOfFish/simplified_phi2" \
    --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": "BucketOfFish/simplified_phi2",
		"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 "BucketOfFish/simplified_phi2" \
        --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": "BucketOfFish/simplified_phi2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use BucketOfFish/simplified_phi2 with Docker Model Runner:
```
docker model run hf.co/BucketOfFish/simplified_phi2
```

simplified_phi2 / config.json

BucketOfFish

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	{
	"_name_or_path": "BucketOfFish/simplified_phi2",
	"architectures": [
	"Phi2Model",
	"Phi2ModelForCausalLM"
	],
	"auto_map": {
	"AutoConfig": "phi2_configuration.Phi2Config",
	"AutoModel": "phi2_model.Phi2Model",
	"AutoModelForCausalLM": "phi2_model.Phi2ModelForCausalLM"
	},
	"model_type": "phi2",
	"torch_dtype": "float16",
	"transformers_version": "4.29.0",

	"vocab_size": 51200,
	"vocab_chunk_for_gpu_efficiency": 64,
	"initial_cos_sin_cache_len": 2048,
	"d_embedding": 2560,
	"n_attn_blocks": 32,
	"n_attn_heads": 32,
	"use_flash_attn": false,
	"use_flash_rotary": false,
	"use_fused_dense": false,
	"attn_pdrop": 0.0,
	"embd_pdrop": 0.0,
	"resid_pdrop": 0.1,
	"layer_norm_epsilon": 1e-05,
	"weight_initialization_range": 0.02,
	"tie_word_embeddings": false,
	"checkpointing": false
	}