Text Generation
Transformers
Safetensors
PEFT
English
reasoning
evidence-grounding
grounded-qa
attribution
fever
hotpotqa
lora
distillation
research
conversational
Instructions to use darcar0/quotebound-27b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use darcar0/quotebound-27b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="darcar0/quotebound-27b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("darcar0/quotebound-27b", device_map="auto") - PEFT
How to use darcar0/quotebound-27b with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use darcar0/quotebound-27b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "darcar0/quotebound-27b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "darcar0/quotebound-27b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/darcar0/quotebound-27b
- SGLang
How to use darcar0/quotebound-27b with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "darcar0/quotebound-27b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "darcar0/quotebound-27b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "darcar0/quotebound-27b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "darcar0/quotebound-27b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use darcar0/quotebound-27b with Docker Model Runner:
docker model run hf.co/darcar0/quotebound-27b
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Download evidence_faithful_reasoning_release_brief.md from darcar0/quotebound-27b: direct link, hf CLI and curl.
- Browser
- Download file 4.79 kB
-
https://huggingface.co/darcar0/quotebound-27b/resolve/main/evidence_faithful_reasoning_release_brief.md
- Command line
-
hf download hf://darcar0/quotebound-27b/evidence_faithful_reasoning_release_brief.md
-
curl -L -o evidence_faithful_reasoning_release_brief.md https://huggingface.co/darcar0/quotebound-27b/resolve/main/evidence_faithful_reasoning_release_brief.md
4.79 kB
| # Quotebound 27B | |
| ## Evidence-Faithful Reasoning Release Brief | |
| Released: 2026-04-07 | |
| Author: darcar0 | |
| Hugging Face model release: | |
| [`darcar0/quotebound-27b`](https://huggingface.co/darcar0/quotebound-27b) | |
| Companion files: | |
| - [`technical_note_evidence_faithful_reasoning.md`](./technical_note_evidence_faithful_reasoning.md) | |
| - [`standalone_holdout_comparison.svg`](./standalone_holdout_comparison.svg) | |
| - [`benchmark_progression.svg`](./benchmark_progression.svg) | |
| ## Executive summary | |
| Quotebound 27B is the standalone model release from Evidence-Faithful | |
| Reasoning: a research-engineering project on reasoning that has to stay | |
| recoverable from the source text rather than asserted on top of it. The | |
| project ships a strict benchmark, the hybrid system that clears that | |
| benchmark under the full contract, and a standalone model trained to carry | |
| the same behavior on its own. | |
| The contract is strict. On every closed packet of source text, the system | |
| has to: | |
| 1. answer correctly, | |
| 2. cite the right evidence units, | |
| 3. quote those units verbatim, and | |
| 4. abstain with `Insufficient evidence.` when the packet does not justify a | |
| claim. | |
| The project ends in two finished results from one frame. The | |
| benchmark-facing winner is a hybrid stack — bridge `checkpoint-2` plus | |
| `deterministic_v3` packet-local quote normalization — that clears every | |
| gate on the frozen held-out `probe_v0` benchmark. The downloadable artifact | |
| is Quotebound 27B on Hugging Face, which beats the earlier bridge model on | |
| a fresh mixed public holdout and roughly doubles raw quote-faithful | |
| behavior at the model level. | |
| ## Quotebound 27B | |
| Quotebound 27B is the strongest standalone model the project produced and | |
| the artifact most readers will load first. It is the first standalone | |
| checkpoint in the project to hold up across multiple evaluation surfaces | |
| beyond the held-out probe. | |
| Fresh 36-task mixed public holdout: | |
| | Stack | Task | Strict | Evidence F1 | Quote F1 | | |
| |---|---:|---:|---:|---:| | |
| | Bridge raw | 0.8611 | 0.2222 | 0.8815 | 0.3343 | | |
| | Quotebound raw | 0.8889 | 0.4444 | 0.9093 | 0.6815 | | |
| | Bridge + `deterministic_v3` | 0.8611 | 0.5833 | 0.8815 | 0.8815 | | |
| | **Quotebound + `deterministic_v3`** | **0.8889** | **0.5833** | **0.9093** | **0.9093** | | |
| Quotebound 27B beats the prior bridge model on task accuracy, evidence F1, | |
| and quote F1 in both raw and normalized form, ties normalized strict, and | |
| roughly doubles raw quote F1 (`0.3343` → `0.6815`) at the model level. | |
| ## Benchmark-facing winner | |
| The benchmark-facing hybrid stack is the strongest full system from the | |
| project. Training moved the model past the older frozen baseline; the | |
| deterministic packet-local normalizer was the finishing repair, closing the | |
| remaining quote-faithful gap without leaving the closed-packet boundary. | |
| | Metric | Frozen probe_v0 | | |
| |---|---:| | |
| | Task success | **1.0000** | | |
| | Strict grounded success | **1.0000** | | |
| | Mean evidence F1 | **1.0000** | | |
| | Mean quote F1 | **1.0000** | | |
| | Verify label accuracy | **1.0000** | | |
| | Grounded QA accuracy | **1.0000** | | |
| | Contrastive consistency | **1.0000** | | |
| | Invalid / missing rate | **0.0000** | | |
| ## Release boundary | |
| The release has two public faces: Quotebound 27B, the standalone model that | |
| loads directly from Hugging Face, and a benchmark-facing hybrid stack that | |
| closes the last quote-faithfulness gap on the frozen held-out probe. The | |
| split is part of the project story, not hidden behind the fine print. | |
| The public release stops at the point where the strongest benchmark-facing | |
| system and the strongest standalone model were both clearly in hand. That | |
| keeps the package centered on finished artifacts rather than on local | |
| variant history. | |
| ## Intended use and boundaries | |
| This is a release for reasoning over closed packets of source text, not a | |
| general-purpose chatbot replacement. It is built for bounded document QA, | |
| claim verification, policy and compliance review, contract reading, and | |
| other settings where every answer has to be justified from a fixed body of | |
| text. | |
| Important boundaries: | |
| - Perfect `probe_v0` belongs to the hybrid stack, not to the standalone | |
| adapter alone. | |
| - The Hugging Face download is the LoRA adapter only; the benchmark-winning | |
| configuration is adapter + `deterministic_v3`. | |
| - Frozen `probe_v0` item-level contents are intentionally not published with | |
| the release. | |
| ## Release surfaces | |
| - Quotebound 27B on Hugging Face: | |
| [`darcar0/quotebound-27b`](https://huggingface.co/darcar0/quotebound-27b) | |
| - Technical note: | |
| [`technical_note_evidence_faithful_reasoning.md`](./technical_note_evidence_faithful_reasoning.md) | |
| - Fresh public holdout chart: | |
| [`standalone_holdout_comparison.svg`](./standalone_holdout_comparison.svg) | |
| - Frozen benchmark progression chart: | |
| [`benchmark_progression.svg`](./benchmark_progression.svg) | |