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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright 2025 SK Telecom Co. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..679c28b --- /dev/null +++ b/README.md @@ -0,0 +1,410 @@ +--- +license: apache-2.0 +license_link: https://huggingface.co/skt/A.X-3.1-Light/blob/main/LICENSE +language: +- en +- ko +pipeline_tag: text-generation +model_id: skt/A.X-3.1-Light +developers: SKT AI Model Lab +model-index: +- name: A.X-3.1-Light + results: + - task: + type: generate_until + name: mmlu + dataset: + name: mmlu (chat CoT) + type: hails/mmlu_no_train + metrics: + - type: exact_match + value: 66.95 + name: exact_match + - task: + type: generate_until + name: kmmlu + dataset: + name: kmmlu (chat CoT) + type: HAERAE-HUB/KMMLU + metrics: + - type: exact_match + value: 61.7 + name: exact_match +base_model: +- skt/A.X-3.1-Light +tags: +- A.X +--- + +# A.X 3.1 Light + +
+ A.X Logo +
+

πŸ€— Models | πŸ–₯️ Github

+ +## A.X 3.1 Light Highlights + + +**A.X 3.1 Light** (pronounced "A dot X") is a light weight LLM optimized for Korean-language understanding and enterprise deployment. +This sovereign AI model was developed entirely in-house by SKT, encompassing model architecture, data curation, and training, all carried out on SKT’s proprietary supercomputing infrastructure, TITAN. +The model was trained from scratch on a high-quality multilingual corpus comprising **1.65 trillion tokens**, with a primary focus on the Korean language. +With a strong emphasis on data quality, A.X 3.1 Light achieves **Pareto-optimal performance among Korean LLMs relative to its training corpus size**, enabling **highly efficient and cost-effective compute usage**. + + +- **Authentic Korean Sovereign AI**: A.X 3.1 Light was trained on a high-quality multilingual datasetβ€”fully curated in-houseβ€”using SKT’s proprietary GPU infrastructure. +- **Highly Efficient Multilingual LLM**: A.X 3.1 Light demonstrates superior performance among open-source Korean LLMs, despite its relatively compact training size of 1.65 trillion tokens. +- **Superior Korean Proficiency**: A.X 3.1 Light achieved a score of **61.7** on the [KMMLU](https://huggingface.co/datasets/HAERAE-HUB/KMMLU): the leading benchmark for Korean-language evaluation and a Korean-specific adaptation of MMLU, outperforming other Korean-specified models. +- **Deep Korean Understanding**: A.X 3.1 Light obtained **27.43** on the [KoBALT-700](https://huggingface.co/datasets/snunlp/KoBALT-700): a benchmark for Korean advanced linguistic tasks, outperforming other Korean-specialized models. +- **Efficient Token Usage**: A.X 3.1 Light requires approximately 33% fewer tokens than GPT-4o to process equivalent Korean inputs, facilitating more cost-effective and computationally efficient inference. +- **Long-Context Handling**: A.X 3.1 Light supports up to **32,768 tokens**. + + +## Core Technologies + +A.X 3.1 Light represents **an efficient sovereign AI model**, developed end-to-end by SKT, encompassing model architecture, data curation, infrastructure deployment, and optimization. + +### Model Architecture Specs + + + + + + + + + + + + + + + + + + + +
Model# Params# Layers# KV-HeadsHidden DimFFN Dim
A.X 3.1 Light7B3232409610880
+ +### High-Quality Data Pipeline & Strategic Mixture + +- We collected and curated a training dataset comprising 20 trillion tokens sourced from diverse domains. +- The entire dataset was processed through SKT’s proprietary data pipeline, incorporating synthetic data generation and comprehensive quality filtering. +- For training A.X 3.1 Light, a total of **1.65 trillion tokens** were utilized, comprising a Korean-focused multilingual corpus. + +### Pareto-Optimal Compute Efficiency + +A.X 3.1 Light achieves 5 to 6 times lower computational cost compared to models with similar performance levels. +Rigorous data curation and two-stage training with STEM-focused data enabled competitive performance at reduced FLOPs. + + +![image](./assets/A.X_3.1_Light_pareto.png) + +## Benchmark Results + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
BenchmarksA.X 3.1 LightKanana-1.5-8BEXAONE-3.5-7.8BQwen2.5-7BQwen3-8B
(w/o reasoning)
KnowledgeKMMLU61.7048.2853.7649.5663.53
CLIcK71.2261.3064.1158.3063.31
KoBALT27.4323.1421.7121.5726.57
MMLU66.9568.8272.2075.4082.89
GeneralKo-MT-Bench78.5676.3081.0661.3164.06
MT-Bench74.3877.6083.5079.3765.69
Instruction
Following		Ko-IFEval70.0469.9665.0160.7373.39
IFEval79.8680.1182.6176.7385.38
MathHRM8K41.7030.8731.8835.1352.50
MATH70.1459.2863.2065.5871.48
Code
HumanEval+73.7876.8376.8374.3977.44
MBPP+61.6467.9964.2968.5062.17
+ +## πŸš€ Quickstart + +### with HuggingFace Transformers + +- `transformers>=4.46.0` or the latest version is required to use `skt/A.X-3.1-Light` +```bash +pip install transformers>=4.46.0 +``` + +#### Example Usage + +```python +import torch +from transformers import AutoModelForCausalLM, AutoTokenizer + +model_name = "skt/A.X-3.1-Light" +model = AutoModelForCausalLM.from_pretrained( + model_name, + torch_dtype=torch.bfloat16, + device_map="auto", +) +model.eval() +tokenizer = AutoTokenizer.from_pretrained(model_name) + +messages = [ + {"role": "system", "content": "당신은 μ‚¬μš©μžκ°€ μ œκ³΅ν•˜λŠ” μ˜μ–΄ λ¬Έμž₯듀을 ν•œκ΅­μ–΄λ‘œ λ²ˆμ—­ν•˜λŠ” AI μ „λ¬Έκ°€μž…λ‹ˆλ‹€."}, + {"role": "user", "content": "The first human went into space and orbited the Earth on April 12, 1961."}, +] +input_ids = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device) + +with torch.no_grad(): + output = model.generate( + input_ids, + max_new_tokens=128, + do_sample=False, + ) + +len_input_prompt = len(input_ids[0]) +response = tokenizer.decode(output[0][len_input_prompt:], skip_special_tokens=True) +print(response) +# Output: +# 1961λ…„ 4μ›” 12일, 졜초의 인간이 μš°μ£Όμ— λ‚˜κ°€ 지ꡬλ₯Ό ꢀ도λ₯Ό λŒμ•˜μŠ΅λ‹ˆλ‹€. +``` + +### with vLLM + +- `vllm>=v0.6.4.post1` or the latest version is required to use tool-use feature +```bash +pip install vllm>=v0.6.4.post1 +# if you don't want to activate tool-use feature, just commenting out below vLLM option +VLLM_OPTION="--enable-auto-tool-choice --tool-call-parser hermes" +vllm serve skt/A.X-3.1-Light $VLLM_OPTION +``` + +#### Example Usage + +```python +from openai import OpenAI + +def call(messages, model): + completion = client.chat.completions.create( + model=model, + messages=messages, + ) + print(completion.choices[0].message) + +client = OpenAI( + base_url="http://localhost:8000/v1", + api_key="api_key" +) +model = "skt/A.X-3.1-Light" +messages = [{"role": "user", "content": "에어컨 여름철 적정 μ˜¨λ„λŠ”? ν•œμ€„λ‘œ λ‹΅λ³€ν•΄μ€˜"}] +call(messages, model) +# Output: +# 에어컨 여름철 적정 μ˜¨λ„λŠ” 24~26λ„μž…λ‹ˆλ‹€. + +messages = [{"role": "user", "content": "What is the appropriate temperature for air conditioning in summer? Respond in a single sentence."}] +call(messages, model) +# Output: +# The appropriate temperature for air conditioning in summer is generally set between 24 to 26Β°C for optimal comfort and energy efficiency. +``` + +#### Examples for tool-use +```python +from openai import OpenAI + + +def call(messages, model): + completion = client.chat.completions.create( + model=model, + messages=messages, + tools=tools + ) + print(completion.choices[0].message) + + +client = OpenAI( + base_url="http://localhost:8000/v1", + api_key="api_key" +) +model = "skt/A.X-3.1-Light" + +calculate_discount = { + "type": "function", + "function": { + "name": "calculate_discount", + "description": "원가격과 ν• μΈμœ¨(νΌμ„ΌνŠΈ λ‹¨μœ„)을 μž…λ ₯λ°›μ•„ ν• μΈλœ κ°€κ²©μ„κ³„μ‚°ν•œλ‹€.", + "parameters": { + "type": "object", + "properties": { + "original_price": { + "type": "number", + "description": "μƒν’ˆμ˜ μ›λž˜ 가격" + }, + "discount_percentage": { + "type": "number", + "description": "μ μš©ν•  ν• μΈμœ¨" + } + }, + "required": ["original_price", "discount_percentage"] + } + } +} +get_exchange_rate = { + "type": "function", + "function": { + "name": "get_exchange_rate", + "description": "두 톡화 κ°„μ˜ ν™˜μœ¨μ„ κ°€μ Έμ˜¨λ‹€.", + "parameters": { + "type": "object", + "properties": { + "base_currency": { + "type": "string", + "description": "The currency to convert from." + }, + "target_currency": { + "type": "string", + "description": "The currency to convert to." + } + }, + "required": ["base_currency", "target_currency"] + } + } +} +tools = [calculate_discount, get_exchange_rate] + +### Slot filling ### +messages = [{"role": "user", "content": "μš°λ¦¬κ°€ 뭘 μ‚¬μ•Όλ˜λŠ”λ° 원가가 57600원인데 직원할인 λ°›μœΌλ©΄ μ–Όλ§ˆμ•Ό?"}] +call(messages, model) +# Output: +# ChatCompletionMessage(content='직원 할인을 μ μš©ν•˜κΈ° μœ„ν•΄μ„œλŠ” ν• μΈμœ¨μ„ μ•Œ 수 μžˆμ–΄μ•Ό ν•©λ‹ˆλ‹€. ν• μΈμœ¨μ„ μ•Œλ €μ£Όμ‹€ 수 μžˆλ‚˜μš”?', role='assistant', function_call=None, tool_calls=[], reasoning_content=None) + + +### Function calling ### +messages = [ + {"role": "user", "content": "μš°λ¦¬κ°€ 뭘 μ‚¬μ•Όλ˜λŠ”λ° 원가가 57600원인데 직원할인 λ°›μœΌλ©΄ μ–Όλ§ˆμ•Ό?"}, + {"role": "assistant", "content": "직원 할인을 μ μš©ν•˜κΈ° μœ„ν•΄μ„œλŠ” ν• μΈμœ¨μ„ μ•Œ 수 μžˆμ–΄μ•Ό ν•©λ‹ˆλ‹€. ν• μΈμœ¨μ„ μ•Œλ €μ£Όμ‹€ 수 μžˆλ‚˜μš”?"}, + {"role": "user", "content": "15% 할인 받을 수 μžˆμ–΄."}, +] +call(messages, model) +# Output: +# ChatCompletionMessage(content=None, role='assistant', function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='chatcmpl-tool-3ebf11847364450daf363039db80cc50', function=Function(arguments='{"original_price": 57600, "discount_percentage": 15}', name='calculate_discount'), type='function')], reasoning_content=None) + + +### Completion ### +messages = [ + {"role": "user", "content": "μš°λ¦¬κ°€ 뭘 μ‚¬μ•Όλ˜λŠ”λ° 원가가 57600원인데 직원할인 λ°›μœΌλ©΄ μ–Όλ§ˆμ•Ό?"}, + {"role": "assistant", "content": ""}, + {"role": "user", "content": "15% 할인 받을 수 μžˆμ–΄."}, + {"role": "tool", "tool_call_id": "random_id", "name": "calculate_discount", "content": "{\"original_price\": 57600, \"discount_percentage\": 15, \"discounted_price\": 48960.0}"} +] +call(messages, model) +# Output: +# ChatCompletionMessage(content='57,600μ›μ˜ μƒν’ˆμ— 15% 할인을 μ μš©ν•˜λ©΄, ν• μΈλœ 가격은 48,960μ›μž…λ‹ˆλ‹€.', role='assistant', function_call=None, tool_calls=[], reasoning_content=None) +``` + +## License + +The `A.X 3.1 Light` model is licensed under `Apache License 2.0`. + +## Citation +``` +@article{SKTAdotX3.1Light, + title={A.X 3.1 Light}, + author={SKT AI Model Lab}, + year={2025}, + url={https://huggingface.co/skt/A.X-3.1-Light} +} +``` + +## Contact + +- Business & Partnership Contact: [a.x@sk.com](a.x@sk.com) \ No newline at end of file diff --git a/imatrix.dat b/imatrix.dat new file mode 100644 index 0000000..ece3d6a --- /dev/null +++ b/imatrix.dat @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3f26416ef37e425575f0407c146fb6493f27b0b52d4bac96b5145ef8dcf59b09 +size 4545778