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CodeLlama-Edge-1.5B

Text Generation
Transformers
PyTorch
ONNX
GGUF
English
llama
causal-lm
code-generation
edge-device
quantized
mobile
text-generation-inference
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metadata
license: apache-2.0
tags:
  - causal-lm
  - code-generation
  - edge-device
  - quantized
  - onnx
  - gguf
  - mobile
language:
  - en
library_name: transformers
pipeline_tag: text-generation
model-index:
  - name: CodeLlama-Edge-1.5B
    results: []

license model size quantized optimized Hugging Face Model

CodeLlama-Edge-1.5B

CodeLlama-Edge-1.5B is an edge-optimized variant of the CodeLlama series, designed to run efficiently on mobile and embedded devices using quantized or distilled formats.

Model Description

  • Model Type: Causal Language Model
  • Base Model: CodeLlama
  • Optimizations: Quantization-aware training, pruning, and edge-device compatibility
  • Parameters: 1.5 Billion
  • Intended Use: On-device coding assistance, embedded systems, low-power environments

Features

  • Token-efficient for code generation
  • Ideal for IDEs, mobile apps, IoT dev tools
  • Low memory and compute footprint

Example Usage 

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("tommytracx/CodeLlama-Edge-1.5B")
model = AutoModelForCausalLM.from_pretrained("tommytracx/CodeLlama-Edge-1.5B")

input_text = "def quicksort(arr):"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=64)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

License

Apache 2.0

Author