add assets identified by bot

assets/alibaba.yaml

@@ -176,3 +176,31 @@
     laws and regulations when deploying the model.
   monitoring: unknown
   feedback: https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5/discussions
+- type: model
+  name: QwQ-32B-Preview
+  organization: Alibaba
+  description: QwQ-32B-Preview is an experimental research model developed by the Qwen Team, focused on advancing AI reasoning capabilities.
+  created_date: 2024-12-08
+  url: https://huggingface.co/Qwen/QwQ-32B-Preview
+  model_card: https://huggingface.co/Qwen/QwQ-32B-Preview
+  modality:
+    explanation: "provides a code snippet with apply_chat_template to show you how to load the tokenizer and model and how to generate contents."
+    value: text; text
+  analysis: unknown
+  size:
+    explanation: "Number of Parameters: 32.5B"
+    value: 32.5B parameters
+  dependencies: [Hugging Face Transformers, Qwen2.5]
+  training_emissions: unknown
+  training_time: unknown
+  training_hardware: unknown
+  quality_control: unknown
+  access:
+    explanation: "Here provides a code snippet with apply_chat_template to show you how to load the tokenizer and model and how to generate contents."
+    value: open
+  license: unknown
+  intended_uses: Demonstrating analytical abilities, focusing on AI reasoning capabilities.
+  prohibited_uses: unknown
+  monitoring: unknown
+  feedback: unknown
+

assets/meta.yaml

@@ -891,3 +891,41 @@
   prohibited_uses: Unknown
   monitoring: Unknown
   feedback: Unknown
+- type: model
+  name: Llama 3.3
+  organization: Meta
+  -_"model_developer: Meta"
+  description: The Meta Llama 3.3 is a multilingual large language model (LLM) that is pretrained and instruction tuned for generative tasks. It is optimized for multilingual dialogue use cases.
+  created_date: 2024-12-06
+  url: https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct
+  model_card: https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct
+  -_"model_release_date: 70B Instruct, December 6, 2024"
+  modality:
+    explanation: "The Llama 3.3 instruction tuned text only model is optimized for multilingual dialogue."
+    value: text; text
+  analysis: Evaluations indicate that Llama 3.3 outperforms many available models on industry benchmarks and includes detailed evaluations of safety risks and specific capabilities.
+  size:
+    explanation: "The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained... model in 70B."
+    value: 70B parameters
+  dependencies: []
+  training_emissions:
+    explanation: "Since 2020, Meta has maintained net zero greenhouse gas emissions in its global operations... therefore the total market-based greenhouse gas emissions for training were 0 tons CO2eq."
+    value: 0 tons CO2eq (market-based)
+  training_time:
+    explanation: "Training Energy Use Training utilized a cumulative of 39.3M GPU hours of computation."
+    value: 7.0M GPU hours
+  training_hardware:
+    explanation: "Training utilized a cumulative of 39.3M GPU hours... on H100-80GB (TDP of 700W) type hardware."
+    value: H100-80GB GPUs
+  quality_control: Employed a multi-faceted approach combining human and synthetic data collection, developed classifiers for high-quality prompts, and incorporated safety mitigations.
+  access:
+    explanation: "A custom commercial license, the Llama 3.3 Community License Agreement, is available..."
+    value: limited
+  license:
+    explanation: "License A custom commercial license, the Llama 3.3 Community License Agreement, is available..."
+    value: Llama 3.3 Community License Agreement
+  intended_uses: Commercial and research use in multiple languages, assistant-like chat, and natural language generation tasks.
+  prohibited_uses: Use violating applicable laws, prohibited by Acceptable Use Policy and Llama 3.3 Community License, and use in unsupported languages without appropriate safety controls.
+  monitoring: Evaluated for safety risks in common use cases, adversarial evaluation datasets, and red teaming exercises with subject-matter experts.
+  feedback: Instructions on how to provide feedback or comments on the model can be found in the model README.
+

assets/uw.yaml

@@ -20,3 +20,33 @@
   prohibited_uses: ''
   monitoring: ''
   feedback: ''
+- type: model
+  name: HunyuanVideo
+  organization: unknown
+  description: "HunyuanVideo, a novel open-source video foundation model that exhibits performance in video generation."
+  created_date: 2024-12-03
+  url: https://huggingface.co/tencent/HunyuanVideo
+  model_card: https://huggingface.co/tencent/HunyuanVideo
+  modality:
+    explanation: "HunyuanVideo (Text-to-Video Model)"; "MLLM after visual instruction finetuning has better image-text alignment"
+    value: text; video
+  analysis: "conducted extensive experiments and implemented a series of targeted designs to ensure high visual quality, motion diversity, text-video alignment, and generation stability"
+  size:
+    explanation: "we successfully trained a video generative model with over 13 billion parameters"
+    value: 13B parameters
+  dependencies: []
+  training_emissions: unknown
+  training_time: unknown
+  training_hardware:
+    explanation: "The model is tested on a single 80G GPU."
+    value: "The model is tested on a single 80G GPU."
+  quality_control: "targeted designs to ensure high visual quality, motion diversity, text-video alignment, and generation stability"
+  access:
+    explanation: "a novel open-source video foundation model"
+    value: open
+  license: unknown
+  intended_uses: unknown
+  prohibited_uses: unknown
+  monitoring: unknown
+  feedback: unknown
+