Instructions to use wesley7137/phi-1_5-scipphi-python-textbook with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use wesley7137/phi-1_5-scipphi-python-textbook with Transformers:

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

pipe = pipeline("text-generation", model="wesley7137/phi-1_5-scipphi-python-textbook", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("wesley7137/phi-1_5-scipphi-python-textbook", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use wesley7137/phi-1_5-scipphi-python-textbook with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "wesley7137/phi-1_5-scipphi-python-textbook"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "wesley7137/phi-1_5-scipphi-python-textbook",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/wesley7137/phi-1_5-scipphi-python-textbook

SGLang

How to use wesley7137/phi-1_5-scipphi-python-textbook 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 "wesley7137/phi-1_5-scipphi-python-textbook" \
    --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": "wesley7137/phi-1_5-scipphi-python-textbook",
		"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 "wesley7137/phi-1_5-scipphi-python-textbook" \
        --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": "wesley7137/phi-1_5-scipphi-python-textbook",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use wesley7137/phi-1_5-scipphi-python-textbook with Docker Model Runner:
```
docker model run hf.co/wesley7137/phi-1_5-scipphi-python-textbook
```

wesley7137 commited on Sep 26, 2023

Commit

203500b

1 Parent(s): ad18b38

Upload MixFormerSequentialForCausalLM

Browse files

Files changed (3) hide show

config.json +26 -0
generation_config.json +4 -0
pytorch_model.bin +3 -0

config.json ADDED Viewed

	@@ -0,0 +1,26 @@

+{
+  "_name_or_path": "microsoft/phi-1_5",
+  "activation_function": "gelu_new",
+  "architectures": [
+    "MixFormerSequentialForCausalLM"
+  ],
+  "auto_map": {
+    "AutoConfig": "microsoft/phi-1_5--configuration_mixformer_sequential.MixFormerSequentialConfig",
+    "AutoModelForCausalLM": "microsoft/phi-1_5--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": "float32",
+  "transformers_version": "4.33.2",
+  "vocab_size": 51200
+}

generation_config.json ADDED Viewed

	@@ -0,0 +1,4 @@

+{
+  "_from_model_config": true,
+  "transformers_version": "4.33.2"
+}

pytorch_model.bin ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:80b7e24d7220de48be36c780f26bc907da84228157c6b75133b21a9fc826cb7f
+size 5673167489