amd/Qwen3.8-2.4T-A95B-Quark-MXFP4开源了新模型

AMD amd/Qwen3.8-2.4T-A95B-Quark-MXFP4 amd/Qwen3.8-2.4T-A95B-Quark-MXFP4 https://huggingface.co/amd/Qwen3.8-2.4T-A95B-Quark-MXFP4

amd/Qwen3.8-2.4T-A95B-Quark-MXFP4 · Hugging Face Hugging Face (https://huggingface.co/) Models (https://huggingface.co/models) Datasets (https://huggingface.co/datasets) Spaces (https://huggingface.co/spaces) Buckets new (https://huggingface.co/storage) Docs (https://huggingface.co/docs) Enterprise (https://huggingface.co/enterprise) Pricing (https://huggingface.co/pricing) Website Tasks (https://huggingface.co/tasks) HuggingChat (https://huggingface.co/chat) Collections (https://huggingface.co/collections) Languages (https://huggingface.co/languages) Organizations (https://huggingface.co/organizations) Community Blog (https://huggingface.co/blog) Posts (https://huggingface.co/posts) Daily Papers (https://huggingface.co/papers) Hardware (https://huggingface.co/hardware) Learn (https://huggingface.co/learn) Discord (https://huggingface.co/join/discord) Forum (https://discuss.huggingface.co/) GitHub (https://github.com/huggingface) Solutions Team & Enterprise (https://huggingface.co/enterprise) Hugging Face PRO (https://huggingface.co/pro) Enterprise Support (https://huggingface.co/support) Inference Providers (https://huggingface.co/inference/models) Inference Endpoints (https://huggingface.co/inference-endpoints) Storage Buckets (https://huggingface.co/storage) Log In (https://huggingface.co/login) Sign Up (https://huggingface.co/join) (https://huggingface.co/amd) amd (https://huggingface.co/amd) / Qwen3.8-2.4T-A95B-Quark-MXFP4 (https://huggingface.co/amd/Qwen3.8-2.4T-A95B-Quark-MXFP4) like 4 Follow AMD 3.12k Text Generation (https://huggingface.co/models?pipeline_tag=text-generation) Transformers (https://huggingface.co/models?library=transformers) Safetensors (https://huggingface.co/models?library=safetensors) English (https://huggingface.co/models?language=en) qwen3_5_moe_text (https://huggingface.co/models?other=qwen3_5_moe_text) conversational (https://huggingface.co/models?other=conversational) 8-bit precision (https://huggingface.co/models?other=8-bit) quark (https://huggingface.co/models?other=quark) Model card (https://huggingface.co/amd/Qwen3.8-2.4T-A95B-Quark-MXFP4) Files Files and versions xet (https://huggingface.co/amd/Qwen3.8-2.4T-A95B-Quark-MXFP4/tree/main) Community 1 (https://huggingface.co/amd/Qwen3.8-2.4T-A95B-Quark-MXFP4/discussions) Deploy Copy to bucket new Use this model Instructions to use amd/Qwen3.8-2.4T-A95B-Quark-MXFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started. Libraries Transformers (https://huggingface.co/amd/Qwen3.8-2.4T-A95B-Quark-MXFP4?library=transformers) How to use amd/Qwen3.8-2.4T-A95B-Quark-MXFP4 with Transformers: # Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="amd/Qwen3.8-2.4T-A95B-Quark-MXFP4") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages) # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("amd/Qwen3.8-2.4T-A95B-Quark-MXFP4") model = AutoModelForCausalLM.from_pretrained("amd/Qwen3.8-2.4T-A95B-Quark-MXFP4", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) Notebooks Google Colab (https://huggingface.co/amd/Qwen3.8-2.4T-A95B-Quark-MXFP4/colab) Kaggle (https://huggingface.co/amd/Qwen3.8-2.4T-A95B-Quark-MXFP4/kaggle) Local Apps Settings (https://huggingface.co/settings/local-apps) vLLM (https://huggingface.co/amd/Qwen3.8-2.4T-A95B-Quark-MXFP4?local-app=vllm) How to use amd/Qwen3.8-2.4T-A95B-Quark-MXFP4 with vLLM: Install from pip and serve model # Install vLLM from pip: pip install vllm # Start the vLLM