Text Generation
Transformers
Safetensors
GGUF
English
code
python
docstring
documentation
code-generation
lora
qlora
smollm2
instruct
causal-lm
conversational
Instructions to use yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator:Q8_0 # Run inference directly in the terminal: llama cli -hf yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator:Q8_0 # Run inference directly in the terminal: llama cli -hf yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator:Q8_0
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator:Q8_0 # Run inference directly in the terminal: ./build/bin/llama cli -hf yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator:Q8_0
Use Docker
docker model run hf.co/yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator:Q8_0
- Llama new
- LM Studio
- Jan
- vLLM
How to use yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator:Q8_0
- SGLang
How to use yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator 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 "yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator" \ --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": "yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator", "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 "yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator" \ --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": "yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator with Ollama:
ollama run hf.co/yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator with Docker Model Runner:
docker model run hf.co/yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator:Q8_0
- Lemonade
How to use yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator:Q8_0
Run and chat with the model
lemonade run user.SmolLM2-1.7B-Instruct-DocstringGenerator-Q8_0
List all available models
lemonade list
- Atomic Chat
Download safetensors/config.json from yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator: direct link, hf CLI and curl.
- Browser
- Download file 952 Bytes
-
https://huggingface.co/yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator/resolve/main/safetensors/config.json
- Command line
-
hf download hf://yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator/safetensors/config.json
-
curl -L -o config.json https://huggingface.co/yezdata/SmolLM2-1.7B-Instruct-DocstringGenerator/resolve/main/safetensors/config.json
952 Bytes
| { | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 1, | |
| "dtype": "float16", | |
| "eos_token_id": 2, | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 2048, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 8192, | |
| "max_position_embeddings": 8192, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 24, | |
| "num_key_value_heads": 32, | |
| "pad_token_id": 2, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_parameters": { | |
| "rope_theta": 130000, | |
| "rope_type": "default" | |
| }, | |
| "tie_word_embeddings": true, | |
| "transformers.js_config": { | |
| "dtype": "q4", | |
| "kv_cache_dtype": { | |
| "fp16": "float16", | |
| "q4f16": "float16" | |
| }, | |
| "use_external_data_format": { | |
| "model.onnx": true, | |
| "model_fp16.onnx": true | |
| } | |
| }, | |
| "transformers_version": "5.13.0", | |
| "use_cache": true, | |
| "vocab_size": 49152 | |
| } | |