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THUDM
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google/gemma-2-2b-it
google
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google/gemma-2-9b-it
google
391
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google/gemma-2-27b-it
google
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microsoft/Phi-3.5-MoE-instruct
microsoft
332
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microsoft/Phi-3.5-mini-instruct
microsoft
289
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microsoft/Phi-3.5-vision-instruct
microsoft
261
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deepseek-ai
250
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Groq/Llama-3-Groq-8B-Tool-Use
Groq
243
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https://huggingface.co/Groq/Llama-3-Groq-8B-Tool-Use/discussions/9
SciPhi/Triplex
SciPhi
219
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null
Sao10K/L3-8B-Stheno-v3.2
Sao10K
194
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null
HuggingFaceM4/Idefics3-8B-Llama3
HuggingFaceM4
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internlm/internlm-xcomposer2d5-7b
internlm
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Qwen/Qwen2-Audio-7B-Instruct
Qwen
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deepseek-ai/DeepSeek-V2-Chat-0628
deepseek-ai
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Nexusflow
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THUDM
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internlm/internlm2_5-7b-chat
internlm
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Groq/Llama-3-Groq-70B-Tool-Use
Groq
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Alibaba-NLP/gte-Qwen2-7B-instruct
Alibaba-NLP
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fireworks-ai/llama-3-firefunction-v2
fireworks-ai
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mlabonne/NeuralDaredevil-8B-abliterated
mlabonne
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Qwen/Qwen2-7B
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numind/NuExtract-large
numind
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ai21labs/AI21-Jamba-1.5-Mini
ai21labs
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arcee-ai
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arcee-ai/Arcee-Agent
arcee-ai
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Qwen
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Sao10K/L3-8B-Lunaris-v1
Sao10K
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akjindal53244
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nothingiisreal/MN-12B-Celeste-V1.9
nothingiisreal
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THUDM/LongWriter-glm4-9b
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Alibaba-NLP/gte-Qwen2-1.5B-instruct
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Tencent-Hunyuan/HunyuanCaptioner
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aifeifei798/DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored
aifeifei798
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intervitens/mini-magnum-12b-v1.1
intervitens
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internlm/internlm2_5-20b-chat
internlm
65
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Qwen/Qwen2-Math-72B-Instruct
Qwen
64
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null
NeverSleep/Lumimaid-v0.2-12B
NeverSleep
64
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hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4
hugging-quants
63
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ClosedCharacter/Peach-9B-8k-Roleplay
ClosedCharacter
63
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null
failspy/Llama-3-8B-Instruct-MopeyMule
failspy
62
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sarvamai/sarvam-2b-v0.5
sarvamai
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dunzhang/stella_en_1.5B_v5
dunzhang
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cyberagent/calm3-22b-chat
cyberagent
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internlm/internlm2_5-7b-chat-1m
internlm
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elyza/Llama-3-ELYZA-JP-8B
elyza
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nyu-visionx/cambrian-8b
nyu-visionx
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Qwen/Qwen2-1.5B
Qwen
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UnfilteredAI
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h2oai/h2o-danube3-4b-chat
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cyberagent/Llama-3.1-70B-Japanese-Instruct-2407
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dnhkng/RYS-XLarge
dnhkng
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Salesforce/xLAM-7b-fc-r
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51
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Nitral-AI/Hathor_Stable-v0.2-L3-8B
Nitral-AI
49
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NeverSleep/Lumimaid-v0.2-8B
NeverSleep
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deepseek-ai/DeepSeek-Coder-V2-Base
deepseek-ai
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Sao10K/L3-8B-Stheno-v3.3-32K
Sao10K
46
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google/recurrentgemma-9b-it
google
45
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deepseek-ai/DeepSeek-Coder-V2-Lite-Base
deepseek-ai
45
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Qwen/Qwen2-Audio-7B
Qwen
45
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IndexTeam/Index-1.9B-Chat
IndexTeam
43
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PleIAs/OCRonos
PleIAs
41
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hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4
hugging-quants
41
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fixie-ai/ultravox-v0_2
fixie-ai
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IlyaGusev/gemma-2-2b-it-abliterated
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Lin-Chen
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arcee-ai/Arcee-Nova
arcee-ai
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google/shieldgemma-2b
google
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SeaLLMs
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Base Model Metadata Sprint

Description

Join us in improving the discoverability and understanding of models on the Hugging Face Hub by adding base_model metadata! This sprint aims to enhance the information available for models derived from, fine-tuned on, or quantized versions of existing base models.

🤗 Strong contributions will win prizes!! 🤗

Why It Matters

Adding base_model metadata helps users:

  1. Easily find models derived from specific architectures
  2. Understand the lineage and potential capabilities of a model
  3. Make informed decisions when choosing models for their projects
  4. Enables a useful Model Tree on the model repo!

image/png

How to Contribute

  1. Access the Sprint CSV
    • Visit the Sprint CSV file on the Hugging Face Hub here
    • This CSV contains models that need to be checked for base_model metadata

image/png

  1. Choose a Model

    • Select a model from the CSV that hasn't been processed yet (PR_CREATED is false)
    • Prioritize models with higher 'likes' counts for maximum impact
  2. Check Existing PRs

    • Before proceeding, check the model's discussion page to ensure no PR for base_model metadata has been created recently
  3. Investigate the Base Model

    • Review the model card and repository for information about the original architecture
    • Look for mentions of base models in the model description or training details
    • If unclear, you may need to do some research on the model's origin
  4. Add the Base Model Metadata (if applicable)

    • Open the model's README.md file on the Hub
    • Add or update the following in the YAML metadata section:
      base_model: HuggingFaceH4/zephyr-7b-beta
      
    • For models derived from multiple base models, use a list:
      base_model:
      - Endevor/InfinityRP-v1-7B
      - l3utterfly/mistral-7b-v0.1-layla-v4
      
    • Optionally, specify the relationship type:
      base_model_relation: quantized
      
      (Valid options: "adapter", "merge", "quantized", "fine-tune")

image/png

  1. Open a Pull Request (if needed)

    • If you've added or updated metadata, submit your changes as a pull request on the model's repository
    • In the PR description, explain your reasoning for adding the base_model metadata
  2. Update the Sprint CSV

    • Update the row for the model you processed:
      • If you created a PR: Set PR_CREATED to "true" and add the PR link to the PR_LINK column
      • If no PR was needed: Set PR_CREATED to "Not Required"
    • Create a pull request to update the Sprint CSV with your changes

Guidelines

  • Focus on accuracy. It's better to mark "Not Required" than to add incorrect metadata.
  • If you're unsure about a base model, you can open a discussion on the model's page to ask the author or community.
  • For models with multiple potential base models, prioritize the most direct ancestor.
  • Remember that some models may not have a clear base model or may not require this metadata. It's okay to mark these as "Not Required".

Resources

Let's work together to make the Hugging Face Hub an even more valuable resource for the AI community!

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