🤗 SmolLM2-135M-QuantLLM

HuggingFaceTB/SmolLM2-135M converted to SAFETENSORS format

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📖 About This Model

This model is HuggingFaceTB/SmolLM2-135M converted to SafeTensors format for use with HuggingFace Transformers and PyTorch.

Property	Value
Base Model	HuggingFaceTB/SmolLM2-135M
Format	SAFETENSORS
Quantization	None (Full Precision)
License	apache-2.0
Created With	QuantLLM

🚀 Quick Start

With Transformers

from transformers import AutoModelForCausalLM, AutoTokenizer

# Load model and tokenizer
model = AutoModelForCausalLM.from_pretrained("codewithdark/SmolLM2-135M-QuantLLM")
tokenizer = AutoTokenizer.from_pretrained("codewithdark/SmolLM2-135M-QuantLLM")

# Generate text
inputs = tokenizer("Once upon a time", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100, do_sample=True)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

With QuantLLM

from quantllm import TurboModel

# Load with automatic optimization
model = TurboModel.from_pretrained("codewithdark/SmolLM2-135M-QuantLLM")

# Generate
response = model.generate("Write a poem about coding")
print(response)

Requirements

pip install transformers torch

📊 Model Details

Property	Value
Original Model	HuggingFaceTB/SmolLM2-135M
Format	SAFETENSORS
Quantization	Full Precision
License	apache-2.0
Export Date	2026-04-29
Exported By	QuantLLM v2.1

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🚀 Created with QuantLLM

Convert any model to GGUF, ONNX, or MLX in one line!

from quantllm import turbo

# Load any HuggingFace model
model = turbo("HuggingFaceTB/SmolLM2-135M")

# Export to any format
model.export("safetensors", quantization="Q4_K_M")

# Push to HuggingFace
model.push("your-repo", format="safetensors")

📚 Documentation · 🐛 Report Issue · 💡 Request Feature

📊 Export Details

Exported with QuantLLM from HuggingFaceTB/SmolLM2-135M (134.5M params).

Property	Value
Format	SafeTensors
Size	541.6 MB
Parameters	134.5M
Dtype	float32

How to use