inclusionAI / Ling-Coder-lite

huggingface.co
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Model's Last Updated: Abril 22 2025
text-generation

Introduction of Ling-Coder-lite

Model Details of Ling-Coder-lite

Ling-Coder-lite

🤗 Hugging Face

Introduction

Ling-Coder-Lite is a MoE LLM provided and open-sourced by InclusionAI, which has 16.8 billion parameters with 2.75 billion activated parameters. Ling-Coder-Lite performs impressively on coding tasks compared to existing models in the industry. Specifically, Ling-Coder-Lite further pre-training from an intermediate checkpoint of Ling-Lite, incorporating an additional 3 trillion tokens. This extended pre-training significantly boosts the coding abilities of Ling-Lite, while preserving its strong performance in general language tasks.

Model Downloads

You can download the following table to see the various parameters for your use case. If you are located in mainland China, we also provide the model on modelscope.cn to speed up the download process.

Model #Total Params #Activated Params Context Length Download
Ling-Coder-lite-base 16.8B 2.75B 4K 🤗 HuggingFace
Ling-Coder-lite 16.8B 2.75B 4K 🤗 HuggingFace
Evaluation

Detailed evaluation results are reported in our technical report [TBD].

Quickstart
🤗 Hugging Face Transformers

Here is a code snippet to show you how to use the chat model with transformers :

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "inclusionAI/Ling-Coder-lite"

model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype="auto",
    device_map="auto",
    trust_remote_code=True
)
tokenizer = AutoTokenizer.from_pretrained(
    model_name, 
    trust_remote_code=True
)

prompt = "Write a quick sort algorithm in python."
messages = [
    {"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)

generated_ids = model.generate(
    **model_inputs,
    max_new_tokens=512
)
generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]

response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)
Deployment

Please refer to Github

License

This code repository is licensed under the MIT License .

Citation

[TBD]

Runs of inclusionAI Ling-Coder-lite on huggingface.co

681
Total runs
0
24-hour runs
226
3-day runs
390
7-day runs
405
30-day runs

More Information About Ling-Coder-lite huggingface.co Model

More Ling-Coder-lite license Visit here:

https://choosealicense.com/licenses/mit

Ling-Coder-lite huggingface.co

Ling-Coder-lite huggingface.co is an AI model on huggingface.co that provides Ling-Coder-lite's model effect (), which can be used instantly with this inclusionAI Ling-Coder-lite model. huggingface.co supports a free trial of the Ling-Coder-lite model, and also provides paid use of the Ling-Coder-lite. Support call Ling-Coder-lite model through api, including Node.js, Python, http.

inclusionAI Ling-Coder-lite online free

Ling-Coder-lite huggingface.co is an online trial and call api platform, which integrates Ling-Coder-lite's modeling effects, including api services, and provides a free online trial of Ling-Coder-lite, you can try Ling-Coder-lite online for free by clicking the link below.

inclusionAI Ling-Coder-lite online free url in huggingface.co:

https://huggingface.co/inclusionAI/Ling-Coder-lite

Ling-Coder-lite install

Ling-Coder-lite is an open source model from GitHub that offers a free installation service, and any user can find Ling-Coder-lite on GitHub to install. At the same time, huggingface.co provides the effect of Ling-Coder-lite install, users can directly use Ling-Coder-lite installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

Ling-Coder-lite install url in huggingface.co:

https://huggingface.co/inclusionAI/Ling-Coder-lite

Url of Ling-Coder-lite

Ling-Coder-lite huggingface.co Url

Provider of Ling-Coder-lite huggingface.co

inclusionAI
ORGANIZATIONS

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