Datasets:

librarian-bots
/

base_model_sprint

modelId stringlengths 11 67	org stringlengths 2 27	likes int64 1 692	PR_CREATED 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

End of preview. Expand in Data Studio

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:

Easily find models derived from specific architectures

Understand the lineage and potential capabilities of a model

Make informed decisions when choosing models for their projects

Enables a useful Model Tree on the model repo!

How to Contribute

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

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

Check Existing PRs

Before proceeding, check the model's discussion page to ensure no PR for base_model metadata has been created recently

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

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")

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

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

Guide to Model Cards on Hugging Face

Base Model Metadata Documentation

Sprint CSV: https://huggingface.co/datasets/librarian-bots/base_model_sprint/blob/main/no_base_model_specified_has_readme_and_chat_template.csv

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

Downloads last month: 30

Size of downloaded dataset files:

72.8 kB

Size of the auto-converted Parquet files:

45.5 kB

Number of rows:

1,329