Instructions to use mrSoul7766/gemma-2b-it-python-code-gen-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mrSoul7766/gemma-2b-it-python-code-gen-adapter with Transformers:

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

pipe = pipeline("text-generation", model="mrSoul7766/gemma-2b-it-python-code-gen-adapter")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mrSoul7766/gemma-2b-it-python-code-gen-adapter")
model = AutoModelForCausalLM.from_pretrained("mrSoul7766/gemma-2b-it-python-code-gen-adapter")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use mrSoul7766/gemma-2b-it-python-code-gen-adapter with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mrSoul7766/gemma-2b-it-python-code-gen-adapter"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mrSoul7766/gemma-2b-it-python-code-gen-adapter",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/mrSoul7766/gemma-2b-it-python-code-gen-adapter

SGLang

How to use mrSoul7766/gemma-2b-it-python-code-gen-adapter 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 "mrSoul7766/gemma-2b-it-python-code-gen-adapter" \
    --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": "mrSoul7766/gemma-2b-it-python-code-gen-adapter",
		"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 "mrSoul7766/gemma-2b-it-python-code-gen-adapter" \
        --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": "mrSoul7766/gemma-2b-it-python-code-gen-adapter",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use mrSoul7766/gemma-2b-it-python-code-gen-adapter with Docker Model Runner:
```
docker model run hf.co/mrSoul7766/gemma-2b-it-python-code-gen-adapter
```

mrSoul7766 commited on Mar 3, 2024

Commit

2ffdedb

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1 Parent(s): 5f953ba

Update README.md

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README.md +13 -14

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@@ -30,7 +30,19 @@ This is the model card of a 🤗 transformers model that has been pushed on the
 ### Direct Use
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-Use this model to generate Python code."
 ```python
 # Load model directly
@@ -53,18 +65,6 @@ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 ```
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-This model is trained on very basic Python code, so it might not be able to handle complex code.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
 ## Training Details
@@ -108,7 +108,6 @@ Use the code below to get started with the model.
 ### Results
-[More Information Needed]
 ```python
 import json
 import pandas as pd

 ### Direct Use
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+Use this model to generate Python code.
+### Out-of-Scope Use
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+This model is trained on very basic Python code, so it might not be able to handle complex code.
+## How to Get Started with the Model
+Use the code below to get started with the model.
 ```python
 # Load model directly
 ```
 ## Training Details
 ### Results
 ```python
 import json
 import pandas as pd