commit ae6b7779cf93cbecfdab8389575eab9d93bc8d17 Author: ModelHub XC Date: Fri Oct 23 08:01:13 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: RedHatAI/Qwen3-14B-NVFP4 Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..ced580a --- /dev/null +++ b/.gitattributes @@ -0,0 +1,54 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bin.* filter=lfs diff=lfs merge=lfs -text +*.bz2 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 +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zstandard filter=lfs diff=lfs merge=lfs -text +*.tfevents* filter=lfs diff=lfs merge=lfs -text +*.db* filter=lfs diff=lfs merge=lfs -text +*.ark* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*data* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.meta filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.index filter=lfs diff=lfs merge=lfs -text + +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.gguf* filter=lfs diff=lfs merge=lfs -text +*.ggml filter=lfs diff=lfs merge=lfs -text +*.llamafile* filter=lfs diff=lfs merge=lfs -text +*.pt2 filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text + +model-00002-of-00003.safetensors filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text +model-00003-of-00003.safetensors filter=lfs diff=lfs merge=lfs -text +model-00001-of-00003.safetensors filter=lfs diff=lfs merge=lfs -text +merges.txt filter=lfs diff=lfs merge=lfs -text +vocab.json filter=lfs diff=lfs merge=lfs -text \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..983ce4c --- /dev/null +++ b/README.md @@ -0,0 +1,396 @@ +--- +tags: +- fp4 +- vllm +language: +- en +- de +- fr +- it +- pt +- hi +- es +- th +pipeline_tag: text-generation +license: apache-2.0 +base_model: Qwen/Qwen3-14B +--- + +# Qwen3-14B-NVFP4 + +## Model Overview +- **Model Architecture:** Qwen/Qwen3-14B + - **Input:** Text + - **Output:** Text +- **Model Optimizations:** + - **Weight quantization:** FP4 + - **Activation quantization:** FP4 +- **Out-of-scope:** Use in any manner that violates applicable laws or regulations (including trade compliance laws). Use in languages other than English. +- **Release Date:** 10/29/2025 +- **Version:** 1.0 +- **Model Developers:** RedHatAI + +This model is a quantized version of [Qwen/Qwen3-14B](https://huggingface.co/Qwen/Qwen3-14B). +It was evaluated on a several tasks to assess the its quality in comparison to the unquatized model. + +### Model Optimizations + +This model was obtained by quantizing the weights and activations of [Qwen/Qwen3-14B](https://huggingface.co/Qwen/Qwen3-14B) to FP4 data type, ready for inference with vLLM>=0.9.1 +This optimization reduces the number of bits per parameter from 16 to 4, reducing the disk size and GPU memory requirements by approximately 75%. + +Only the weights and activations of the linear operators within transformers blocks are quantized using [LLM Compressor](https://github.com/vllm-project/llm-compressor). + +## Deployment + +### Use with vLLM + +This model can be deployed efficiently using the [vLLM](https://docs.vllm.ai/en/latest/) backend, as shown in the example below. + +```python +from vllm import LLM, SamplingParams +from transformers import AutoTokenizer + +model_id = "RedHatAI/Qwen3-14B-NVFP4" +number_gpus = 1 + +sampling_params = SamplingParams(temperature=0.6, top_p=0.9, max_tokens=256) + +tokenizer = AutoTokenizer.from_pretrained(model_id) + +messages = [ + {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"}, + {"role": "user", "content": "Who are you?"}, +] + +prompts = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False) + +llm = LLM(model=model_id, tensor_parallel_size=number_gpus) + +outputs = llm.generate(prompts, sampling_params) + +generated_text = outputs[0].outputs[0].text +print(generated_text) +``` + +vLLM aslo supports OpenAI-compatible serving. See the [documentation](https://docs.vllm.ai/en/latest/) for more details. + +## Creation + +This model was created by applying [LLM Compressor with calibration samples from UltraChat](https://github.com/vllm-project/llm-compressor/blob/main/examples/quantization_w4a4_fp4/llama3_example.py), as presented in the code snipet below. + +
+ +```python +from datasets import load_dataset +from transformers import AutoModelForCausalLM, AutoTokenizer + +from llmcompressor import oneshot +from llmcompressor.modifiers.quantization import QuantizationModifier +from llmcompressor.utils import dispatch_for_generation + +MODEL_ID = "Qwen/Qwen3-14B" + +# Load model. +model = AutoModelForCausalLM.from_pretrained(MODEL_ID, torch_dtype="auto") +tokenizer = AutoTokenizer.from_pretrained(MODEL_ID) + +DATASET_ID = "HuggingFaceH4/ultrachat_200k" +DATASET_SPLIT = "train_sft" + +# Select number of samples. 512 samples is a good place to start. +# Increasing the number of samples can improve accuracy. +NUM_CALIBRATION_SAMPLES = 512 +MAX_SEQUENCE_LENGTH = 2048 + +# Load dataset and preprocess. +ds = load_dataset(DATASET_ID, split=f"{DATASET_SPLIT}[:{NUM_CALIBRATION_SAMPLES}]") +ds = ds.shuffle(seed=42) + +def preprocess(example): + return { + "text": tokenizer.apply_chat_template( + example["messages"], + tokenize=False, + ) + } + +ds = ds.map(preprocess) + +# Tokenize inputs. +def tokenize(sample): + return tokenizer( + sample["text"], + padding=False, + max_length=MAX_SEQUENCE_LENGTH, + truncation=True, + add_special_tokens=False, + ) + +ds = ds.map(tokenize, remove_columns=ds.column_names) + +# Configure the quantization algorithm and scheme. +# In this case, we: +# * quantize the weights to fp4 with per group 16 via ptq +# * calibrate a global_scale for activations, which will be used to +# quantize activations to fp4 on the fly +recipe = [ + QuantizationModifier( + ignore=["re:.*lm_head.*"], + config_groups={ + "group_0": { + "targets": ["Linear"], + "weights": { + "num_bits": 4, + "type": "float", + "strategy": "tensor_group", + "group_size": 16, + "symmetric": True, + "observer": "mse", + }, + "input_activations": { + "num_bits": 4, + "type": "float", + "strategy": "tensor_group", + "group_size": 16, + "symmetric": True, + "dynamic": "local", + "observer": "minmax", + }, + } + }, + ) +] + +# Save to disk in compressed-tensors format. +SAVE_DIR = MODEL_ID.rstrip("/").split("/")[-1] + "-NVFP4" + +# Apply quantization. +oneshot( + model=model, + dataset=ds, + recipe=recipe, + max_seq_length=MAX_SEQUENCE_LENGTH, + num_calibration_samples=NUM_CALIBRATION_SAMPLES, + output_dir=SAVE_DIR, +) + +print("\n\n") +print("========== SAMPLE GENERATION ==============") +dispatch_for_generation(model) +input_ids = tokenizer("Hello my name is", return_tensors="pt").input_ids.to("cuda") +output = model.generate(input_ids, max_new_tokens=100) +print(tokenizer.decode(output[0])) +print("==========================================\n\n") + +model.save_pretrained(SAVE_DIR, save_compressed=True) +tokenizer.save_pretrained(SAVE_DIR) + +``` + +
+ +## Evaluation + +This model was evaluated on the well-known OpenLLM v1, OpenLLM v2 and HumanEval_64 benchmarks using [lm-evaluation-harness](https://github.com/neuralmagic/lm-evaluation-harness). The Reasoning evals were done using [ligheval](https://github.com/neuralmagic/lighteval). + +### Accuracy + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
CategoryMetricQwen3-14BQwen3-14B-NVFP4 (this model)Recovery
OpenLLM V1arc_challenge67.3267.0699.61
gsm8k88.7088.2599.49
hellaswag79.6278.2498.27
mmlu78.8677.2397.93
truthfulqa_mc258.5958.4999.83
winogrande73.7273.80100.11
Average74.4773.8599.16
OpenLLM V2BBH (3-shot)59.4556.7895.51
MMLU-Pro (5-shot)44.3941.1592.70
MuSR (0-shot)38.6237.8397.95
IFEval (0-shot)89.4590.41101.07
GPQA (0-shot)27.4326.5996.94
Math-|v|-5 (4-shot)57.3353.4093.14
Average52.7851.0396.68
CodingHumanEval_64 pass@290.7489.8799.04
ReasoningAIME24 (0-shot)75.8665.5286.34
AIME25 (0-shot)68.9765.5295.00
GPQA (Diamond, 0-shot)64.9760.4093.00
Average69.9363.8191.45
+ + + +### Reproduction + +The results were obtained using the following commands: +
+ +#### OpenLLM v1 +``` +lm_eval \ + --model vllm \ + --model_args pretrained="RedHatAI/Qwen3-14B-NVFP4",dtype=auto,max_model_len=4096,tensor_parallel_size=2,enable_chunked_prefill=True,enforce_eager=True\ + --apply_chat_template \ + --fewshot_as_multiturn \ + --tasks openllm \ + --batch_size auto +``` + + +#### OpenLLM v2 +``` +lm_eval \ + --model vllm \ + --model_args pretrained="RedHatAI/Qwen3-14B-NVFP4",dtype=auto,max_model_len=4096,tensor_parallel_size=2,enable_chunked_prefill=True,enforce_eager=True\ + --apply_chat_template \ + --fewshot_as_multiturn \ + --tasks leaderboard \ + --batch_size auto +``` + +#### HumanEval_64 +``` +lm_eval \ + --model vllm \ + --model_args pretrained="RedHatAI/Qwen3-14B-NVFP4",dtype=auto,max_model_len=4096,tensor_parallel_size=2,enable_chunked_prefill=True,enforce_eager=True\ + --apply_chat_template \ + --fewshot_as_multiturn \ + --tasks humaneval_64_instruct \ + --batch_size auto +``` + +#### LightEval +``` +# --- model_args.yaml --- +cat > model_args.yaml <<'YAML' +model_parameters: + model_name: "RedHatAI/Qwen3-14B-NVFP4" + dtype: auto + gpu_memory_utilization: 0.9 + tensor_parallel_size: 2 + max_model_length: 40960 + generation_parameters: + seed: 42 + temperature: 0.6 + top_k: 20 + top_p: 0.95 + min_p: 0.0 + max_new_tokens: 32768 +YAML + +lighteval vllm model_args.yaml \ + "lighteval|aime24|0,lighteval|aime25|0,lighteval|gpqa:diamond|0" \ + --max-samples -1 \ + --output-dir out_dir + +``` +
\ No newline at end of file diff --git a/added_tokens.json b/added_tokens.json new file mode 100644 index 0000000..b54f913 --- /dev/null +++ b/added_tokens.json @@ -0,0 +1,28 @@ +{ + "": 151668, + "": 151658, + "": 151666, + "": 151667, + "": 151657, + "": 151665, + "<|box_end|>": 151649, + "<|box_start|>": 151648, + "<|endoftext|>": 151643, + "<|file_sep|>": 151664, + "<|fim_middle|>": 151660, + "<|fim_pad|>": 151662, + "<|fim_prefix|>": 151659, + "<|fim_suffix|>": 151661, + "<|im_end|>": 151645, + "<|im_start|>": 151644, + "<|image_pad|>": 151655, + "<|object_ref_end|>": 151647, + "<|object_ref_start|>": 151646, + "<|quad_end|>": 151651, + "<|quad_start|>": 151650, + "<|repo_name|>": 151663, + "<|video_pad|>": 151656, + "<|vision_end|>": 151653, + "<|vision_pad|>": 151654, + "<|vision_start|>": 151652 +} diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..01be9b3 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,89 @@ +{%- if tools %} + {{- '<|im_start|>system\n' }} + {%- if messages[0].role == 'system' %} + {{- messages[0].content + '\n\n' }} + {%- endif %} + {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within XML tags:\n" }} + {%- for tool in tools %} + {{- "\n" }} + {{- tool | tojson }} + {%- endfor %} + {{- "\n\n\nFor each function call, return a json object with function name and arguments within XML tags:\n\n{\"name\": , \"arguments\": }\n<|im_end|>\n" }} +{%- else %} + {%- if messages[0].role == 'system' %} + {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }} + {%- endif %} +{%- endif %} +{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %} +{%- for message in messages[::-1] %} + {%- set index = (messages|length - 1) - loop.index0 %} + {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('') and message.content.endswith('')) %} + {%- set ns.multi_step_tool = false %} + {%- set ns.last_query_index = index %} + {%- endif %} +{%- endfor %} +{%- for message in messages %} + {%- if message.content is string %} + {%- set content = message.content %} + {%- else %} + {%- set content = '' %} + {%- endif %} + {%- if (message.role == "user") or (message.role == "system" and not loop.first) %} + {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }} + {%- elif message.role == "assistant" %} + {%- set reasoning_content = '' %} + {%- if message.reasoning_content is string %} + {%- set reasoning_content = message.reasoning_content %} + {%- else %} + {%- if '' in content %} + {%- set reasoning_content = content.split('')[0].rstrip('\n').split('')[-1].lstrip('\n') %} + {%- set content = content.split('')[-1].lstrip('\n') %} + {%- endif %} + {%- endif %} + {%- if loop.index0 > ns.last_query_index %} + {%- if loop.last or (not loop.last and reasoning_content) %} + {{- '<|im_start|>' + message.role + '\n\n' + reasoning_content.strip('\n') + '\n\n\n' + content.lstrip('\n') }} + {%- else %} + {{- '<|im_start|>' + message.role + '\n' + content }} + {%- endif %} + {%- else %} + {{- '<|im_start|>' + message.role + '\n' + content }} + {%- endif %} + {%- if message.tool_calls %} + {%- for tool_call in message.tool_calls %} + {%- if (loop.first and content) or (not loop.first) %} + {{- '\n' }} + {%- endif %} + {%- if tool_call.function %} + {%- set tool_call = tool_call.function %} + {%- endif %} + {{- '\n{"name": "' }} + {{- tool_call.name }} + {{- '", "arguments": ' }} + {%- if tool_call.arguments is string %} + {{- tool_call.arguments }} + {%- else %} + {{- tool_call.arguments | tojson }} + {%- endif %} + {{- '}\n' }} + {%- endfor %} + {%- endif %} + {{- '<|im_end|>\n' }} + {%- elif message.role == "tool" %} + {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %} + {{- '<|im_start|>user' }} + {%- endif %} + {{- '\n\n' }} + {{- content }} + {{- '\n' }} + {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %} + {{- '<|im_end|>\n' }} + {%- endif %} + {%- endif %} +{%- endfor %} +{%- if add_generation_prompt %} + {{- '<|im_start|>assistant\n' }} + {%- if enable_thinking is defined and enable_thinking is false %} + {{- '\n\n\n\n' }} + {%- endif %} +{%- endif %} \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..0f38081 --- /dev/null +++ b/config.json @@ -0,0 +1,118 @@ +{ + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 151643, + "eos_token_id": 151645, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 5120, + "initializer_range": 0.02, + "intermediate_size": 17408, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + 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