commit 8e24c0d12df88cc03db3802d6cfd8afab148d3ee Author: ModelHub XC Date: Sat Oct 10 12:52:27 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: Euraika/EuroLLM-22B-Instruct-GPTQ Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text 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100644 index 0000000..f776656 --- /dev/null +++ b/README.md @@ -0,0 +1,161 @@ +--- +license: apache-2.0 +language: +- en +- de +- fr +- it +- es +- pt +- pl +- nl +- tr +- sv +- cs +- el +- hu +- ro +- fi +- uk +- sk +- da +- bg +- no +- sl +- lt +- lv +- et +- hr +- ga +- mt +base_model: utter-project/EuroLLM-22B-Instruct-2512 +library_name: transformers +tags: +- gptq +- 4bit +- quantized +- eurollm +- multilingual +- european +- instruct +pipeline_tag: text-generation +model_creator: UTTER Project +quantized_by: Euraika +--- + +# EuroLLM-22B-Instruct GPTQ (4-bit) + +This is a 4-bit GPTQ quantized version of [utter-project/EuroLLM-22B-Instruct-2512](https://huggingface.co/utter-project/EuroLLM-22B-Instruct-2512). + +## Model Details + +| Attribute | Value | +|-----------|-------| +| Original Model | EuroLLM-22B-Instruct-2512 | +| Quantization | GPTQ 4-bit | +| Group Size | 128 | +| Activation Order | desc_act=True | +| Calibration Samples | 512 | +| Sequence Length | 1024 | +| Calibration Dataset | OpenHermes-2.5 (ChatML format) | +| Size | ~14GB | + +## Quantization Configuration + +```json +{ + "bits": 4, + "group_size": 128, + "desc_act": true, + "damp_percent": 0.01, + "sym": true, + "true_sequential": true +} +``` + +## Quantization Quality + +The quantization achieved excellent loss values across all 53 transformer layers: +- Attention projections: 10⁻⁵ to 10⁻⁶ range +- MLP layers: 10⁻⁵ range +- No error explosion or instability + +## Languages Supported + +EuroLLM supports all 24 official EU languages plus additional European languages: +Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Greek, Hungarian, Irish, Italian, Latvian, Lithuanian, Maltese, Norwegian, Polish, Portuguese, Romanian, Slovak, Slovenian, Spanish, Swedish, Turkish, Ukrainian + +## Usage + +### With GPTQModel (Recommended) + +```python +from gptqmodel import GPTQModel +from transformers import AutoTokenizer + +model = GPTQModel.load("Euraika/EuroLLM-22B-Instruct-GPTQ", device="cuda:0") +tokenizer = AutoTokenizer.from_pretrained("Euraika/EuroLLM-22B-Instruct-GPTQ") + +prompt = """<|im_start|>system +You are a helpful AI assistant.<|im_end|> +<|im_start|>user +Explain quantum computing in simple terms.<|im_end|> +<|im_start|>assistant +""" + +inputs = tokenizer(prompt, return_tensors="pt").to("cuda:0") +outputs = model.generate(**inputs, max_new_tokens=256, temperature=0.7, top_p=0.9) +print(tokenizer.decode(outputs[0], skip_special_tokens=True)) +``` + +### With vLLM + +```python +from vllm import LLM, SamplingParams + +llm = LLM(model="Euraika/EuroLLM-22B-Instruct-GPTQ", quantization="gptq") +sampling_params = SamplingParams(temperature=0.7, top_p=0.9, max_tokens=256) + +outputs = llm.generate(["Your prompt here"], sampling_params) +``` + +### With Transformers + AutoGPTQ + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer + +model = AutoModelForCausalLM.from_pretrained( + "Euraika/EuroLLM-22B-Instruct-GPTQ", + device_map="auto" +) +tokenizer = AutoTokenizer.from_pretrained("Euraika/EuroLLM-22B-Instruct-GPTQ") +``` + +## Chat Template + +This model uses the ChatML format: + +``` +<|im_start|>system +{system_message}<|im_end|> +<|im_start|>user +{user_message}<|im_end|> +<|im_start|>assistant +{assistant_message}<|im_end|> +``` + +## Hardware Requirements + +- **Minimum**: 16GB VRAM (RTX 4080, RTX A4000) +- **Recommended**: 24GB VRAM (RTX 4090, RTX A5000, RTX 6000) +- Supports multi-GPU inference via device_map="auto" + +## Credits + +- **Original Model**: [UTTER Project](https://huggingface.co/utter-project) - EuroLLM team +- **Quantization**: Euraika using GPTQModel v5.6.12 +- **Calibration Dataset**: [OpenHermes-2.5](https://huggingface.co/datasets/teknium/OpenHermes-2.5) + +## License + +Apache 2.0 (same as base model) diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..5dcd1d5 --- /dev/null +++ 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