modelId
stringlengths
11
67
org
stringlengths
2
27
likes
int64
1
692
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bool
2 classes
PR_LINK
stringclasses
2 values
mistralai/Mistral-Large-Instruct-2407
mistralai
692
false
null
openbmb/MiniCPM-V-2_6
openbmb
596
false
null
THUDM/glm-4-9b-chat
THUDM
528
false
null
google/gemma-2-2b-it
google
459
true
null
google/gemma-2-9b-it
google
391
true
null
google/gemma-2-27b-it
google
366
true
null
microsoft/Phi-3.5-MoE-instruct
microsoft
332
false
null
microsoft/Phi-3.5-mini-instruct
microsoft
289
false
null
microsoft/Phi-3.5-vision-instruct
microsoft
261
false
null
deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct
deepseek-ai
250
false
null
Groq/Llama-3-Groq-8B-Tool-Use
Groq
243
true
https://huggingface.co/Groq/Llama-3-Groq-8B-Tool-Use/discussions/9
SciPhi/Triplex
SciPhi
219
false
null
Sao10K/L3-8B-Stheno-v3.2
Sao10K
194
false
null
HuggingFaceM4/Idefics3-8B-Llama3
HuggingFaceM4
175
false
null
internlm/internlm-xcomposer2d5-7b
internlm
169
false
null
Qwen/Qwen2-Audio-7B-Instruct
Qwen
168
false
null
deepseek-ai/DeepSeek-V2-Chat-0628
deepseek-ai
158
false
null
Nexusflow/Athene-70B
Nexusflow
148
true
https://huggingface.co/Nexusflow/Athene-70B/discussions/11
THUDM/glm-4-9b-chat-1m
THUDM
146
false
null
internlm/internlm2_5-7b-chat
internlm
145
false
null
Groq/Llama-3-Groq-70B-Tool-Use
Groq
141
false
null
Alibaba-NLP/gte-Qwen2-7B-instruct
Alibaba-NLP
139
false
null
fireworks-ai/llama-3-firefunction-v2
fireworks-ai
126
false
null
mlabonne/NeuralDaredevil-8B-abliterated
mlabonne
123
false
null
Qwen/Qwen2-7B
Qwen
115
false
null
numind/NuExtract-large
numind
110
false
null
Qwen/Qwen2-1.5B-Instruct
Qwen
107
false
null
UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
UCLA-AGI
104
false
null
Sao10K/L3-70B-Euryale-v2.1
Sao10K
103
false
null
qnguyen3/nanoLLaVA-1.5
qnguyen3
94
false
null
ai21labs/AI21-Jamba-1.5-Mini
ai21labs
85
false
null
arcee-ai/Arcee-Spark
arcee-ai
84
false
null
arcee-ai/Arcee-Agent
arcee-ai
82
false
null
Qwen/Qwen2-0.5B
Qwen
79
false
null
Sao10K/L3-8B-Lunaris-v1
Sao10K
77
false
null
AnatoliiPotapov/T-lite-instruct-0.1
AnatoliiPotapov
77
false
null
NousResearch/Hermes-2-Theta-Llama-3-70B
NousResearch
76
false
null
akjindal53244/Llama-3.1-Storm-8B
akjindal53244
76
false
null
nothingiisreal/MN-12B-Celeste-V1.9
nothingiisreal
72
false
null
UCLA-AGI/Llama-3-Instruct-8B-SPPO-Iter3
UCLA-AGI
72
false
null
THUDM/LongWriter-glm4-9b
THUDM
68
false
null
Alibaba-NLP/gte-Qwen2-1.5B-instruct
Alibaba-NLP
68
false
null
Tencent-Hunyuan/HunyuanCaptioner
Tencent-Hunyuan
67
false
null
aifeifei798/DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored
aifeifei798
66
false
null
intervitens/mini-magnum-12b-v1.1
intervitens
66
false
null
internlm/internlm2_5-20b-chat
internlm
65
false
null
Qwen/Qwen2-Math-72B-Instruct
Qwen
64
false
null
NeverSleep/Lumimaid-v0.2-12B
NeverSleep
64
false
null
hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4
hugging-quants
63
false
null
ClosedCharacter/Peach-9B-8k-Roleplay
ClosedCharacter
63
false
null
failspy/Llama-3-8B-Instruct-MopeyMule
failspy
62
false
null
sarvamai/sarvam-2b-v0.5
sarvamai
61
false
null
dunzhang/stella_en_1.5B_v5
dunzhang
59
false
null
cyberagent/calm3-22b-chat
cyberagent
59
false
null
internlm/internlm2_5-7b-chat-1m
internlm
58
false
null
elyza/Llama-3-ELYZA-JP-8B
elyza
58
false
null
nyu-visionx/cambrian-8b
nyu-visionx
57
false
null
Qwen/Qwen2-1.5B
Qwen
56
false
null
UnfilteredAI/NSFW-3B
UnfilteredAI
55
false
null
h2oai/h2o-danube3-4b-chat
h2oai
55
false
null
cyberagent/Llama-3.1-70B-Japanese-Instruct-2407
cyberagent
53
false
null
dnhkng/RYS-XLarge
dnhkng
52
false
null
Salesforce/xLAM-7b-fc-r
Salesforce
51
false
null
Nitral-AI/Hathor_Stable-v0.2-L3-8B
Nitral-AI
49
false
null
NeverSleep/Lumimaid-v0.2-8B
NeverSleep
48
false
null
deepseek-ai/DeepSeek-Coder-V2-Base
deepseek-ai
47
false
null
Sao10K/L3-8B-Stheno-v3.3-32K
Sao10K
46
false
null
google/recurrentgemma-9b-it
google
45
false
null
deepseek-ai/DeepSeek-Coder-V2-Lite-Base
deepseek-ai
45
false
null
Qwen/Qwen2-Audio-7B
Qwen
45
false
null
IndexTeam/Index-1.9B-Chat
IndexTeam
43
false
null
PleIAs/OCRonos
PleIAs
41
false
null
hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4
hugging-quants
41
false
null
fixie-ai/ultravox-v0_2
fixie-ai
40
false
null
IlyaGusev/gemma-2-2b-it-abliterated
IlyaGusev
40
false
null
nothingiisreal/L3-8B-Celeste-V1.2
nothingiisreal
39
false
null
OuteAI/Lite-Mistral-150M-v2-Instruct
OuteAI
39
false
null
TheDrummer/Gemmasutra-Mini-2B-v1
TheDrummer
37
false
null
Lin-Chen/sharegpt4video-8b
Lin-Chen
37
false
null
PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct
PatronusAI
37
false
null
arcee-ai/Arcee-Nova
arcee-ai
36
false
null
google/shieldgemma-2b
google
36
false
null
SeaLLMs/SeaLLMs-v3-7B-Chat
SeaLLMs
36
false
null
openbmb/MiniCPM-V-2_6-int4
openbmb
35
false
null
nothingiisreal/Celeste-12B-V1.6
nothingiisreal
35
false
null
Sao10K/Llama-3.1-8B-Stheno-v3.4
Sao10K
35
false
null
Replete-AI/Replete-Coder-Llama3-8B
Replete-AI
34
false
null
Orenguteng/Llama-3.1-8B-Lexi-Uncensored
Orenguteng
34
false
null
DAMO-NLP-SG/VideoLLaMA2-7B
DAMO-NLP-SG
34
false
null
numind/NuExtract-tiny
numind
33
false
null
PowerInfer/TurboSparse-Mixtral
PowerInfer
33
false
null
arcee-ai/Llama-3-SEC-Chat
arcee-ai
32
false
null
aws-prototyping/MegaBeam-Mistral-7B-512k
aws-prototyping
32
false
null
failspy/Meta-Llama-3-70B-Instruct-abliterated-v3.5
failspy
32
false
null
Salesforce/xLAM-1b-fc-r
Salesforce
32
false
null
sarvamai/shuka_v1
sarvamai
32
false
null
BAAI/Bunny-v1_1-Llama-3-8B-V
BAAI
31
false
null
KISTI-KONI/KONI-Llama3-8B-Instruct-20240729
KISTI-KONI
31
false
null
TheDrummer/Smegmma-9B-v1
TheDrummer
31
false
null
Qwen/Qwen2-Math-7B-Instruct
Qwen
31
false
null

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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