datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
glaive-function-calling-v2glaive_toolcall_enBorrowed from: https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2
You can use it in LLaMA Factory by specifying dataset: glaive_toolcall_en.
glaive-function-callingThis dataset consists of 52k samples generated through Glaive for the task of function calling, in the following format-
SYSTEM: You are an helpful assistant who has access to the following functions to help the user, you can use the functions if needed-
{
JSON function definiton
}
USER: user message
ASSISTANT: assistant message
Function call invocations are formatted as-
ASSISTANT: <functioncall> {json function call}
Response to the function call is formatted as-
FUNCTION RESPONSE: {json… See the full description on the dataset page: https://huggingface.co/datasets/glaiveai/glaive-function-calling.glaive-function-calling-v2-sharegptThe glaive-function-calling-v2 dataset in sharegpt format.
You can use it in LLaMA Factory by specifying --dataset glaive_toolcall_100k.
glaive-function-calling-v2Modified version of the glaiveai/glaive-function-calling-v2 dataset
All samples in the glaive dataset is converted into the following format for better interoperability
[
{
"role":"system",
"content":"You are a helpful assistant with access to the functions.",
"functions":[
{
"name":"generate_password",
"description":"Generate a random password with specified criteria",
"parameters":{… See the full description on the dataset page: https://huggingface.co/datasets/Dulsara/glaive-function-calling-v2.glaive_toolcall_enBorrowed from: https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2
You can use it in LLaMA Factory by specifying dataset: glaive_toolcall_en.
noteflow-research-pilots
Keep the failed attempts. Check the artifact.
Versioned public development evidence from Robot Reel × Skills Anywhere × EvalArc, recorded 14 September 2026 on an NVIDIA L40S, with separate scripted Harbor controls on CPU and separate GPU context-control and agent-requested MCP handoff cohorts recorded 19 September 2026. This is an inspectable engineering casebook, not a held-out benchmark or training corpus with established efficacy.
Configuration
Actual experiment
What… See the full description on the dataset page: https://huggingface.co/datasets/glayguo/noteflow-research-pilots.pine-of-glass-sessions
Coding agent session traces for thomasmustier/pine-of-glass-sessions
This dataset contains redacted coding agent session traces collected while working on tmustier/pine-of-glass. The traces were exported with pi-share-hf from a local pi workspace. The traces were filtered to keep only sessions that passed deterministic redaction and LLM review.
Data description
Each *.jsonl file is a redacted pi session. Sessions are stored as JSON Lines files where each line is a… See the full description on the dataset page: https://huggingface.co/datasets/thomasmustier/pine-of-glass-sessions.glaive_toolcall_zhBorrowed from: https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2
Translated by GPT-3.5.
You can use it in LLaMA Factory by specifying dataset: glaive_toolcall_zh.
fin-glaive
Fin-Glaive: 645K Financial Instruction and Reasoning Examples
Fin-Glaive is a large-scale English dataset for financial instruction tuning, financial question answering, and reasoning-focused language-model post-training. It contains 645,232 question–reasoning–answer examples mined from Glaive Reasoning v1 20M.
The dataset and its role in the post-training pipeline are described in Data-Centric Post-Training for Financial Reasoning: Mining, Distillation, and Verifiable Learning.… See the full description on the dataset page: https://huggingface.co/datasets/whoisjiji/fin-glaive.glaive-function-calling-v2-ru-parsed
Glaive Function Calling V2 Parsed (RU)
This dataset is a fork of an original mizinovmv/glaive-function-calling-v2-ru.
Structure
train (102860 rows)
messages
functions
test (9681 rows)
messages
functions
Messages field contains JSON string with list of messages. Each message has role (one of: system, user, assistant, function_call, function_response) and content (message string) fields.
Functions field contains JSON string with list of functions for current chat… See the full description on the dataset page: https://huggingface.co/datasets/korotkov/glaive-function-calling-v2-ru-parsed.startup-interviewsglaive-function-calling-v2-parsed
Glaive Function Calling V2 Parsed
This dataset is a fork of an original - glaiveai/glaive-function-calling-v2.
Structure
train (100199 rows)
messages
functions
test (12553 rows)
messages
functions
Messages field contains JSON string with list of messages. Each message has role (one of: system, user, assistant, function_call, function_response) and content (message string) fields.
Functions field contains JSON string with list of functions for current chat (their… See the full description on the dataset page: https://huggingface.co/datasets/korotkov/glaive-function-calling-v2-parsed.shlyokavitsa-pairs
Shlyokavitsa → Cyrillic restoration pairs
210,236 (Latin, Cyrillic) phrase pairs for restoring shlyokavitsa (Bulgarian typed on a
Latin keyboard) back into Cyrillic. Built from Bulgarian Wikipedia, so it can be shared
under the same licence as its source.
{"latin": "sreshta se na dalbochina okolo", "cyrillic": "среща се на дълбочина около", "n_words": 5, "page_id": 1041}
Filed under translation because that is the closest category the Hub offers, but the task is
script… See the full description on the dataset page: https://huggingface.co/datasets/glassbox/shlyokavitsa-pairs.evalarc-independent-swe
Independent-source SWE workflow records
36 Qwen3-8B attempts compare four fixed workflows on three public SWE-bench
Verified tasks. There are no accepted attempts: 31 have assessable native
reports and five retain an upstream infrastructure flag, so their task outcome
is uncertain. Eight attempts produced nonempty patches. One generation request
has incomplete usage.
Inspect the interactive report
· English method · 中文方法
· Offline review and exact raw records
This dataset… See the full description on the dataset page: https://huggingface.co/datasets/glayguo/evalarc-independent-swe.SFT_glaive_toolcall_en
Preparing Your Dataset
Once you’ve decided that fine-tuning is the best approach—after optimizing your prompt as much as possible and identifying remaining model issues—you’ll need to prepare training data. Start by creating a diverse set of example conversations that mirror those the model will handle during production.
Each example should follow this structure below, consisting of a list of messages. Each message must include a role, content, and an optional name. Make sure some… See the full description on the dataset page: https://huggingface.co/datasets/GreenNode/SFT_glaive_toolcall_en.glaive-function-calling-v2glaive-tool-use-reasoning-ar
Arabic Glaive Tool-Use Reasoning
Arabic translation and augmentation of the Glaive Function Calling data for research on Arabic function calling, tool selection, argument generation, and tool-call verification.
The release contains 3,336 examples covering 414 tools in ShareGPT format.
Dataset Structure
Each example contains:
{
"tools": [...],
"conversations": [...]
}
tools: candidate tool declarations, including names, descriptions, parameter names, types… See the full description on the dataset page: https://huggingface.co/datasets/Makeen-AraFC/glaive-tool-use-reasoning-ar.glaiveai_glaive-code-assistant-gemini-2.0-flash-thinking-exp-1219-CustomShareGPT
glaiveai_glaive-code-assistant-gemini-2.0-flash-thinking-exp-1219-CustomShareGPT
glaiveai/glaive-code-assistant with responses regenerated with gemini-2.0-flash-thinking-exp-1219.
Generation Details
If BlockedPromptException, StopCandidateException, or InvalidArgument was returned, the sample was skipped.
If ["candidates"][0]["safety_ratings"] == "SAFETY" the sample was skipped.
If ["candidates"][0]["finish_reason"] != 1 the sample was skipped.
model =… See the full description on the dataset page: https://huggingface.co/datasets/PJMixers-Dev/glaiveai_glaive-code-assistant-gemini-2.0-flash-thinking-exp-1219-CustomShareGPT.glaive-function-calling-v2Instruct-Summary
Dataset Card for "Instruct-Summary"
This dataset is a combination of kmfoda/booksum, samsum, mosaicml/dolly_hhrlhf and yahma/alpaca-cleaned.
RLHF_glaive_toolcall_en
Preparing Your Reward Dataset
Once you’ve decided that fine-tuning is the best approach—after optimizing your prompt as much as possible and identifying remaining model issues—you’ll need to prepare training data. Start by creating a diverse set of example conversations that mirror those the model will handle during production.
Each example should follow this structure below, consisting of a list of messages. Each message must include a role, content, and an optional name. Make sure… See the full description on the dataset page: https://huggingface.co/datasets/GreenNode/RLHF_glaive_toolcall_en.mirror-glaive-function-calling-v2glados
Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More… See the full description on the dataset page: https://huggingface.co/datasets/slimShaders/glados.