From f2d0e9e237df91450f03a1e7f0934dc38d6dee04 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sun, 20 Sep 2026 06:15:15 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: RedHatAI/Llama-3.1-8B-Instruct-NVFP4 Source: Original Platform --- .gitattributes | 51 + README.md | 395 ++++++ chat_template.jinja | 109 ++ config.json | 85 ++ configuration.json | 1 + generation_config.json | 12 + model-00001-of-00002.safetensors | 3 + model-00002-of-00002.safetensors | 3 + model.safetensors.index.json | 971 ++++++++++++++ recipe.yaml | 42 + special_tokens_map.json | 16 + tokenizer.json | 3 + tokenizer_config.json | 2062 ++++++++++++++++++++++++++++++ 13 files changed, 3753 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 configuration.json create mode 100644 generation_config.json create mode 100644 model-00001-of-00002.safetensors create mode 100644 model-00002-of-00002.safetensors create mode 100644 model.safetensors.index.json create mode 100644 recipe.yaml create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..de7fbe1 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,51 @@ +*.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-00002.safetensors filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text +model-00001-of-00002.safetensors 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..32f40f8 --- /dev/null +++ b/README.md @@ -0,0 +1,395 @@ +--- +tags: +- fp4 +- vllm +language: +- en +- de +- fr +- it +- pt +- hi +- es +- th +pipeline_tag: text-generation +license: llama3.1 +base_model: meta-llama/Meta-Llama-3.1-8B-Instruct +--- + +# Meta-Llama-3.1-8B-Instruct-NVFP4 + +## Model Overview +- **Model Architecture:** Meta-Llama-3.1 + - **Input:** Text + - **Output:** Text +- **Model Optimizations:** + - **Weight quantization:** FP4 + - **Activation quantization:** FP4 +- **Intended Use Cases:** Intended for commercial and research use in multiple languages. Similarly to [Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct), this models is intended for assistant-like chat. +- **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:** 10/23/2025 +- **Version:** 1.0 +- **License(s):** [llama3.1](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B/blob/main/LICENSE) +- **Model Developers:** RedHatAI + +This model is a quantized version of [Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct). +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 [Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) 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/Meta-Llama-3.1-8B-Instruct-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.modifiers.smoothquant import SmoothQuantModifier +from llmcompressor.utils import dispatch_for_generation + +MODEL_ID = "meta-llama/Meta-Llama-3-8B-Instruct" + +# 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 +smoothing_strength = 0.5 +recipe = [ + SmoothQuantModifier(smoothing_strength=smoothing_strength), + 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. All evaluations were conducted using [lm-evaluation-harness](https://github.com/neuralmagic/lm-evaluation-harness). + +### Accuracy + + + + + + + + + + + + + + + + + + + + + + +
CategoryMetricMeta-Llama-3.1-8B-InstructLlama-3.1-8B-Instruct-NVFP4 (this model)Recovery
OpenLLM V1arc_challenge_llama83.3582.3298.76
gsm8k_llama78.1779.30101.45
hellaswag78.4378.0199.46
mmlu_llama69.3765.9595.07
mmlu_cot_llama72.8668.6094.15
truthfulqa_mc255.0952.9596.12
winogrande75.7774.0397.70
Average73.2971.5997.68
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
CategoryMetricMeta-Llama-3.1-8B-InstructRedHatAI/Llama-3.1-8B-Instruct-NVFP4 (this model)Recovery (%)
OpenLLM V2MMLU-Pro (5-shot)37.6934.4391.35
IFEval (0-shot)80.9479.9898.81
BBH (3-shot)50.7648.6295.78
Math-|v|-5 (4-shot)22.0514.6566.44
GPQA (0-shot)28.4427.9498.24
MuSR (0-shot)38.1037.8399.29
Average43.0040.5894.37
CodingHumanEval_64 pass@271.9071.4499.36
+ + + +### Reproduction + +The results were obtained using the following commands: + +
+ +#### MMLU_LLAMA +``` +lm_eval \ + --model vllm \ + --model_args pretrained="RedHatAI/Meta-Llama-3.1-8B-Instruct-NVFP4",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1,enable_chunked_prefill=True,enforce_eager=True \ + --tasks mmlu_llama \ + --apply_chat_template \ + --fewshot_as_multiturn \ + --batch_size auto +``` + +#### MMLU_COT_LLAMA +``` +lm_eval \ + --model vllm \ + --model_args pretrained="RedHatAI/Meta-Llama-3.1-8B-Instruct-NVFP4",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1,enable_chunked_prefill=True,enforce_eager=True \ + --tasks mmlu_cot_llama \ + --apply_chat_template \ + --fewshot_as_multiturn \ + --batch_size auto +``` + +#### ARC-Challenge +``` +lm_eval \ + --model vllm \ + --model_args pretrained="RedHatAI/Meta-Llama-3.1-8B-Instruct-NVFP4",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1,enable_chunked_prefill=True,enforce_eager=True \ + --tasks arc_challenge_llama \ + --apply_chat_template \ + --batch_size auto +``` + +#### GSM-8K +``` +lm_eval \ + --model vllm \ + --model_args pretrained="RedHatAI/Meta-Llama-3.1-8B-Instruct-NVFP4",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1,enable_chunked_prefill=True,enforce_eager=True \ + --tasks gsm8k_llama \ + --apply_chat_template \ + --fewshot_as_multiturn \ + --batch_size auto +``` + +#### Hellaswag +``` +lm_eval \ + --model vllm \ + --model_args pretrained="RedHatAI/Meta-Llama-3.1-8B-Instruct-NVFP4",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1,enable_chunked_prefill=True,enforce_eager=True \ + --tasks hellaswag \ + --apply_chat_template \ + --fewshot_as_multiturn \ + --batch_size auto +``` + +#### Winogrande +``` +lm_eval \ + --model vllm \ + --model_args pretrained="RedHatAI/Meta-Llama-3.1-8B-Instruct-NVFP4",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1,enable_chunked_prefill=True,enforce_eager=True \ + --tasks winogrande \ + --apply_chat_template \ + --fewshot_as_multiturn \ + --batch_size auto +``` + +#### TruthfulQA +``` +lm_eval \ + --model vllm \ + --model_args pretrained="RedHatAI/Meta-Llama-3.1-8B-Instruct-NVFP4",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1,enable_chunked_prefill=True,enforce_eager=True \ + --tasks truthfulqa \ + --apply_chat_template \ + --fewshot_as_multiturn \ + --batch_size auto +``` + +#### OpenLLM v2 +``` +lm_eval \ + --model vllm \ + --model_args pretrained="RedHatAI/Meta-Llama-3.1-8B-Instruct-NVFP4",dtype=auto,max_model_len=4096,tensor_parallel_size=1,enable_chunked_prefill=True,enforce_eager=True\ + --apply_chat_template \ + --fewshot_as_multiturn \ + --tasks leaderboard \ + --batch_size auto +``` + +#### HumanEval and HumanEval_64 +``` +lm_eval \ + --model vllm \ + --model_args pretrained="RedHatAI/Meta-Llama-3.1-8B-Instruct-NVFP4",dtype=auto,max_model_len=4096,tensor_parallel_size=1,enable_chunked_prefill=True,enforce_eager=True\ + --apply_chat_template \ + --fewshot_as_multiturn \ + --tasks humaneval_64_instruct \ + --batch_size auto +``` + +
diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..33089ac --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,109 @@ +{{- bos_token }} +{%- if custom_tools is defined %} + {%- set tools = custom_tools %} +{%- endif %} +{%- if not tools_in_user_message is defined %} + {%- set tools_in_user_message = true %} +{%- endif %} +{%- if not date_string is defined %} + {%- set date_string = "26 Jul 2024" %} +{%- endif %} +{%- if not tools is defined %} + {%- set tools = none %} +{%- endif %} + +{#- This block extracts the system message, so we can slot it into the right place. #} +{%- if messages[0]['role'] == 'system' %} + {%- set system_message = messages[0]['content']|trim %} + {%- set messages = messages[1:] %} +{%- else %} + {%- set system_message = "" %} +{%- endif %} + +{#- System message + builtin tools #} +{{- "<|start_header_id|>system<|end_header_id|>\n\n" }} +{%- if builtin_tools is defined or tools is not none %} + {{- "Environment: ipython\n" }} +{%- endif %} +{%- if builtin_tools is defined %} + {{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}} +{%- endif %} +{{- "Cutting Knowledge Date: December 2023\n" }} +{{- "Today Date: " + date_string + "\n\n" }} +{%- if tools is not none and not tools_in_user_message %} + {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }} + {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }} + {{- "Do not use variables.\n\n" }} + {%- for t in tools %} + {{- t | tojson(indent=4) }} + {{- "\n\n" }} + {%- endfor %} +{%- endif %} +{{- system_message }} +{{- "<|eot_id|>" }} + +{#- Custom tools are passed in a user message with some extra guidance #} +{%- if tools_in_user_message and not tools is none %} + {#- Extract the first user message so we can plug it in here #} + {%- if messages | length != 0 %} + {%- set first_user_message = messages[0]['content']|trim %} + {%- set messages = messages[1:] %} + {%- else %} + {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }} +{%- endif %} + {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}} + {{- "Given the following functions, please respond with a JSON for a function call " }} + {{- "with its proper arguments that best answers the given prompt.\n\n" }} + {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }} + {{- "Do not use variables.\n\n" }} + {%- for t in tools %} + {{- t | tojson(indent=4) }} + {{- "\n\n" }} + {%- endfor %} + {{- first_user_message + "<|eot_id|>"}} +{%- endif %} + +{%- for message in messages %} + {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %} + {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }} + {%- elif 'tool_calls' in message %} + {%- if not message.tool_calls|length == 1 %} + {{- raise_exception("This model only supports single tool-calls at once!") }} + {%- endif %} + {%- set tool_call = message.tool_calls[0].function %} + {%- if builtin_tools is defined and tool_call.name in builtin_tools %} + {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}} + {{- "<|python_tag|>" + tool_call.name + ".call(" }} + {%- for arg_name, arg_val in tool_call.arguments | items %} + {{- arg_name + '="' + arg_val + '"' }} + {%- if not loop.last %} + {{- ", " }} + {%- endif %} + {%- endfor %} + {{- ")" }} + {%- else %} + {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}} + {{- '{"name": "' + tool_call.name + '", ' }} + {{- '"parameters": ' }} + {{- tool_call.arguments | tojson }} + {{- "}" }} + {%- endif %} + {%- if builtin_tools is defined %} + {#- This means we're in ipython mode #} + {{- "<|eom_id|>" }} + {%- else %} + {{- "<|eot_id|>" }} + {%- endif %} + {%- elif message.role == "tool" or message.role == "ipython" %} + {{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }} + {%- if message.content is mapping or message.content is iterable %} + {{- message.content | tojson }} + {%- else %} + {{- message.content }} + {%- endif %} + {{- "<|eot_id|>" }} + {%- endif %} +{%- endfor %} +{%- if add_generation_prompt %} + {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }} +{%- endif %} diff --git a/config.json b/config.json new file mode 100644 index 0000000..37f8016 --- /dev/null +++ b/config.json @@ -0,0 +1,85 @@ +{ + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 128000, + "dtype": "bfloat16", + "eos_token_id": [ + 128001, + 128008, + 128009 + ], + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 4096, + "initializer_range": 0.02, + "intermediate_size": 14336, + "max_position_embeddings": 131072, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 32, + "num_hidden_layers": 32, + "num_key_value_heads": 8, + "pretraining_tp": 1, + "quantization_config": { + "config_groups": { + "group_0": { + "format": "nvfp4-pack-quantized", + "input_activations": { + "actorder": null, + "block_structure": null, + "dynamic": "local", + "group_size": 16, + "num_bits": 4, + "observer": "minmax", + "observer_kwargs": 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SmoothQuantModifier: + smoothing_strength: 0.5 + mappings: + - !!python/tuple + - ['re:.*q_proj', 're:.*k_proj', 're:.*v_proj'] + - re:.*input_layernorm + - !!python/tuple + - ['re:.*gate_proj', 're:.*up_proj'] + - re:.*post_attention_layernorm + ignore: [] + QuantizationModifier: + config_groups: + group_0: + targets: [Linear] + weights: + num_bits: 4 + type: float + symmetric: true + group_size: 16 + strategy: tensor_group + block_structure: null + dynamic: false + actorder: null + observer: mse + observer_kwargs: {} + input_activations: + num_bits: 4 + type: float + symmetric: true + group_size: 16 + strategy: tensor_group + block_structure: null + dynamic: local + actorder: null + observer: minmax + observer_kwargs: {} + output_activations: null + format: null + targets: [Linear] + ignore: ['re:.*lm_head.*'] diff --git a/special_tokens_map.json b/special_tokens_map.json new file mode 100644 index 0000000..02ee80b --- /dev/null +++ b/special_tokens_map.json @@ -0,0 +1,16 @@ +{ + 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