Text Generation
Transformers
TensorBoard
Safetensors
gemma3_text
Generated from Trainer
sft
trl
conversational
text-generation-inference
Instructions to use Plofski/myPythonCoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Plofski/myPythonCoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Plofski/myPythonCoder") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Plofski/myPythonCoder") model = AutoModelForCausalLM.from_pretrained("Plofski/myPythonCoder") 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 Plofski/myPythonCoder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Plofski/myPythonCoder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Plofski/myPythonCoder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Plofski/myPythonCoder
- SGLang
How to use Plofski/myPythonCoder 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 "Plofski/myPythonCoder" \ --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": "Plofski/myPythonCoder", "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 "Plofski/myPythonCoder" \ --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": "Plofski/myPythonCoder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Plofski/myPythonCoder with Docker Model Runner:
docker model run hf.co/Plofski/myPythonCoder
| {# Unsloth Chat template fixes #} | |
| {{ bos_token }} | |
| {%- if messages[0]['role'] == 'system' -%} | |
| {%- if messages[0]['content'] is string -%} | |
| {%- set first_user_prefix = messages[0]['content'] + ' | |
| ' -%} | |
| {%- else -%} | |
| {%- set first_user_prefix = messages[0]['content'][0]['text'] + ' | |
| ' -%} | |
| {%- endif -%} | |
| {%- set loop_messages = messages[1:] -%} | |
| {%- else -%} | |
| {%- set first_user_prefix = "" -%} | |
| {%- set loop_messages = messages -%} | |
| {%- endif -%} | |
| {%- for message in loop_messages -%} | |
| {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%} | |
| {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }} | |
| {%- endif -%} | |
| {%- if (message['role'] == 'assistant') -%} | |
| {%- set role = "model" -%} | |
| {%- else -%} | |
| {%- set role = message['role'] -%} | |
| {%- endif -%} | |
| {{ '<start_of_turn>' + role + ' | |
| ' + (first_user_prefix if loop.first else "") }} | |
| {%- if message['content'] is string -%} | |
| {{ message['content'] | trim }} | |
| {%- elif message['content'] is iterable -%} | |
| {%- for item in message['content'] -%} | |
| {%- if item['type'] == 'image' -%} | |
| {{ '<start_of_image>' }} | |
| {%- elif item['type'] == 'text' -%} | |
| {{ item['text'] | trim }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- elif message['content'] is defined -%} | |
| {{ raise_exception("Invalid content type") }} | |
| {%- endif -%} | |
| {{ '<end_of_turn> | |
| ' }} | |
| {%- endfor -%} | |
| {%- if add_generation_prompt -%} | |
| {{'<start_of_turn>model | |
| '}} | |
| {%- endif -%} | |
| {# Copyright 2025-present Unsloth. Apache 2.0 License. #} |