Instructions to use dphn/dolphin-phi-2-kensho with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dphn/dolphin-phi-2-kensho with Transformers:

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

pipe = pipeline("text-generation", model="dphn/dolphin-phi-2-kensho", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("dphn/dolphin-phi-2-kensho", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use dphn/dolphin-phi-2-kensho with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dphn/dolphin-phi-2-kensho"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dphn/dolphin-phi-2-kensho",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/dphn/dolphin-phi-2-kensho

SGLang

How to use dphn/dolphin-phi-2-kensho 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 "dphn/dolphin-phi-2-kensho" \
    --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": "dphn/dolphin-phi-2-kensho",
		"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 "dphn/dolphin-phi-2-kensho" \
        --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": "dphn/dolphin-phi-2-kensho",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use dphn/dolphin-phi-2-kensho with Docker Model Runner:
```
docker model run hf.co/dphn/dolphin-phi-2-kensho
```

DavidGF commited on Mar 5, 2024

Commit

cd357c3

verified ·

1 Parent(s): 0a2cee8

Update modeling_phi.py

Browse files

Files changed (1) hide show

modeling_phi.py +65 -18

modeling_phi.py CHANGED Viewed

@@ -928,27 +928,74 @@ class PhiModel(PhiPreTrainedModel):
         return hidden_states
 group_definitions = [
-    list(range(0, 4)),  # Indices for the first group
-    list(range(4, 8)), # Indices for the second group, with overlap
-    list(range(8, 12)), # Indices for the second group, with overlap
-    list(range(12, 16)), # Indices for the second group, with overlap
-    list(range(16, 20)), # Indices for the second group, with overlap
-    list(range(20, 24)), # Indices for the second group, with overlap
-    list(range(24, 28)), # Indices for the second group, with overlap
-    list(range(28, 32)), # Indices for the second group, with overlap
-    # Add more groups as needed
 ]
 repetitions = [
-    1, # Repetitions for the first group
-    2, # Repetitions for the second group
-    2, # Repetitions for the second group
-    2, # Repetitions for the second group
-    2, # Repetitions for the second group
-    2, # Repetitions for the second group
-    2, # Repetitions for the second group
-    1, # Repetitions for the second group
-    # Add more repetition counts as needed
 ]
 class AdvancedSharedLayerModule(nn.Module):

         return hidden_states
 group_definitions = [
+    list(range(0, 1)),  # Indices for the 1st group
+    list(range(1, 2)),
+    list(range(2, 3)),
+    list(range(3, 4)),
+    list(range(4, 5)),
+    list(range(5, 6)),
+    list(range(6, 7)),
+    list(range(7, 8)),
+    list(range(8, 9)),
+    list(range(9, 10)),
+    list(range(10, 11)),
+    list(range(11, 12)),
+    list(range(12, 13)),
+    list(range(13, 14)),
+    list(range(14, 15)),
+    list(range(15, 16)),
+    list(range(16, 17)),
+    list(range(17, 18)),
+    list(range(18, 19)),
+    list(range(19, 20)),
+    list(range(20, 21)),
+    list(range(21, 22)),
+    list(range(22, 23)),
+    list(range(23, 24)),
+    list(range(24, 25)),
+    list(range(25, 26)),
+    list(range(26, 27)),
+    list(range(27, 28)),
+    list(range(28, 29)),
+    list(range(29, 30)),
+    list(range(30, 31)),
+    list(range(31, 32)),
 ]
 repetitions = [
+    1,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2,
+    1,
 ]
 class AdvancedSharedLayerModule(nn.Module):