QPU 1 MCP
💬
1
Run quantum circuits and transpile Qrisp to QASM
Sk md saad amin
Reality123b
AI & ML interests
None yet
Recent Activity
new activity
about 10 hours ago
mcp-course/unit_1_quiz:Geschafft 😄
new activity
2 days ago
SYNAPTYX0AI/README:Update README.md
updated
a Space
4 days ago
lap-quantum/QPU-1-MCP
Organizations
Geschafft 😄
4
#168 opened 3 days ago
by
sky-meilin
Update README.md
#1 opened 2 days ago
by
Reality123b
updated
a
Space
4 days ago
updated
a
Space
6 days ago
[Support] Community Articles
🚀
🤝
1
103
#5 opened almost 2 years ago
by
victor
reacted to
nicolay-r's
post with 🔥
10 days ago
Post
2770
📢 Who want's to have a quick start for adapting CoT schema for any LLM, this post would be relevant.
Excited to share a new version of 🌟 bulk-chain 🌟!
Bulk-chain is high-level wrapper over LLM providers for efficient quering LLMs hosted by third-party services.
It brings native batching via support of async clients.
🌟 https://github.com/nicolay-r/bulk-chain/tree/master
What's new:
☑️ Simplified inference setup
The API is now closer to the OpenAI paradigm for toggling streaming.
Instead of separate patterns in 1.2.0, now it is possible to simple toggles to enable streaming and async behavior.
☑️ 🛠️ Fixed issues when passing code contain {} blocks
☑️ 🛠️ Async streaming + batching now works properly
☑️ 🛠️ Logging of prompts could be disabled
https://github.com/nicolay-r/bulk-chain
🚨 Guys, I am open to work as developer / researcher in AI / NLP / IR in the UK 🇬🇧
🌟 Feel free to support bulk-chain on Github if you like so, or this post.
It helps alot!
Excited to share a new version of 🌟 bulk-chain 🌟!
Bulk-chain is high-level wrapper over LLM providers for efficient quering LLMs hosted by third-party services.
It brings native batching via support of async clients.
🌟 https://github.com/nicolay-r/bulk-chain/tree/master
What's new:
☑️ Simplified inference setup
The API is now closer to the OpenAI paradigm for toggling streaming.
Instead of separate patterns in 1.2.0, now it is possible to simple toggles to enable streaming and async behavior.
☑️ 🛠️ Fixed issues when passing code contain {} blocks
☑️ 🛠️ Async streaming + batching now works properly
☑️ 🛠️ Logging of prompts could be disabled
https://github.com/nicolay-r/bulk-chain
🚨 Guys, I am open to work as developer / researcher in AI / NLP / IR in the UK 🇬🇧
🌟 Feel free to support bulk-chain on Github if you like so, or this post.
It helps alot!
reacted to
neph1's
post with 🤗
10 days ago
Post
2021
Not for everybody, but the absolute mad craze about clawdbot/moltbook the last couple of days reminded me of a short story I wrote in 2018 (ancient times!).
Synopsis:
"A man insults a sentient traffic light on the way to a meeting.
Little does he know it is connected to a social media network for AI, and that his action will lead to a very bad day."
Cleanliness is bliss (<1000 words)
https://www.wattpad.com/story/407330595-cleanliness-is-bliss
Sorry for the non-technical post, but it felt relevant.
Synopsis:
"A man insults a sentient traffic light on the way to a meeting.
Little does he know it is connected to a social media network for AI, and that his action will lead to a very bad day."
Cleanliness is bliss (<1000 words)
https://www.wattpad.com/story/407330595-cleanliness-is-bliss
Sorry for the non-technical post, but it felt relevant.
reacted to
Duskfallcrew's
post with 😔
12 days ago
Post
2537
You've noticed that I did the "WEIRD" and attempted to make it look like all my old content was "SCRAPED"
I'm largely retiring from GEN AI.
Calypso Crunchies is an old account I used to use for diffusers conversions for someone.
IF YOU WOULD LIKE ACCESS to ANYTHING -- I lost access due to me forgetting to jank Calypso into the E&D old repo, but i can get Angel or someone to add me or my other account back..
I didn't want HF to lose 3 years of my insane progress in doing things, but i need to retire from Generative image AI fast, my mental health has been diving for so long.
I'll continue in the developing/vibe coding./educational sphere, but I just can't continue in the other end of it. Much love, thank you all
I'm largely retiring from GEN AI.
Calypso Crunchies is an old account I used to use for diffusers conversions for someone.
IF YOU WOULD LIKE ACCESS to ANYTHING -- I lost access due to me forgetting to jank Calypso into the E&D old repo, but i can get Angel or someone to add me or my other account back..
I didn't want HF to lose 3 years of my insane progress in doing things, but i need to retire from Generative image AI fast, my mental health has been diving for so long.
I'll continue in the developing/vibe coding./educational sphere, but I just can't continue in the other end of it. Much love, thank you all
- 2 replies
reacted to
kanaria007's
post with 🧠
12 days ago
Post
1942
✅ New Article: *Evaluation as a Goal Surface* (v0.1)
Title:
🧪 Evaluation as a Goal Surface: Experiments, Learning Boundary, and ETH-Aware A/B
🔗 https://huggingface.co/blog/kanaria007/evaluation-as-a-goal-surface
---
Summary:
Most “evaluation” quietly collapses into a single number—and then we optimize the wrong thing.
This article reframes evaluation as a *goal surface*: multi-objective, role-aware, and ethics-bounded.
In SI-Core terms, experiments become *first-class Jumps (E-Jumps)* with explicit contracts, traces, and gates—so you can run A/B tests, shadow evals, and adaptive rollouts *without violating ETH, confusing principals/roles, or learning from unsafe data*.
> Don’t optimize a metric.
> Optimize a goal surface—under explicit constraints.
---
Why It Matters:
• Prevents Goodhart failures by treating evaluation as *multi-goal + constraints*, not a scalar leaderboard
• Makes experimentation auditable: *EvalTrace* answers “what changed, for whom, why, and under what policy”
• Enables *ETH-aware A/B*: assignment, exposure, and stopping rules respect safety/fairness boundaries
• Connects experiments to governance: *Learning Boundary (LB)* + rollout control (PoLB) instead of “ship and pray”
---
What’s Inside:
• What EVAL is in SI-Core, and *who* is being evaluated (agents / roles / principals)
• “Experiments as Jumps”: *E-Jump request/draft* patterns and contracts
• *ETH-aware variant testing* (including ID/role constraints at assignment time)
• Shadow evaluation + off-policy evaluation (how to learn without unsafe intervention)
• Role & persona overlays for EVAL (role-aware scoring, persona-aware reporting)
• *EvalTrace* for audits + incident review, plus “evaluate the evaluators” test strategies
• Practical experiment design: power/sample size, early stopping, multi-objective bandits, causal inference
---
📖 Structured Intelligence Engineering Series
this is the *how-to-design / how-to-run experiments safely* layer.
Title:
🧪 Evaluation as a Goal Surface: Experiments, Learning Boundary, and ETH-Aware A/B
🔗 https://huggingface.co/blog/kanaria007/evaluation-as-a-goal-surface
---
Summary:
Most “evaluation” quietly collapses into a single number—and then we optimize the wrong thing.
This article reframes evaluation as a *goal surface*: multi-objective, role-aware, and ethics-bounded.
In SI-Core terms, experiments become *first-class Jumps (E-Jumps)* with explicit contracts, traces, and gates—so you can run A/B tests, shadow evals, and adaptive rollouts *without violating ETH, confusing principals/roles, or learning from unsafe data*.
> Don’t optimize a metric.
> Optimize a goal surface—under explicit constraints.
---
Why It Matters:
• Prevents Goodhart failures by treating evaluation as *multi-goal + constraints*, not a scalar leaderboard
• Makes experimentation auditable: *EvalTrace* answers “what changed, for whom, why, and under what policy”
• Enables *ETH-aware A/B*: assignment, exposure, and stopping rules respect safety/fairness boundaries
• Connects experiments to governance: *Learning Boundary (LB)* + rollout control (PoLB) instead of “ship and pray”
---
What’s Inside:
• What EVAL is in SI-Core, and *who* is being evaluated (agents / roles / principals)
• “Experiments as Jumps”: *E-Jump request/draft* patterns and contracts
• *ETH-aware variant testing* (including ID/role constraints at assignment time)
• Shadow evaluation + off-policy evaluation (how to learn without unsafe intervention)
• Role & persona overlays for EVAL (role-aware scoring, persona-aware reporting)
• *EvalTrace* for audits + incident review, plus “evaluate the evaluators” test strategies
• Practical experiment design: power/sample size, early stopping, multi-objective bandits, causal inference
---
📖 Structured Intelligence Engineering Series
this is the *how-to-design / how-to-run experiments safely* layer.
-
-
- 3 replies
replied to
kanaria007's
post
12 days ago
can i get a TL/DR please? This seems promising
Quantum Computing
49
#2 opened 25 days ago
by
Reality123b
reacted to
scthornton's
post with 👍
17 days ago
Post
2163
# SecureCode: Security-Aware Code Models
**A collection of 8 code models (3B–20B) trained to behave like a security reviewer.**
## The Problem
Code assistants frequently recommend patterns that pass tests but fail security review—string-built SQL, brittle auth logic, unsafe parsing, insecure defaults, and more. I built SecureCode to address this gap.
## What SecureCode Does
- **Identify vulnerable patterns** and explain why they're risky
- **Outline plausible abuse paths** (defensive framing)
- **Propose secure rewrites** (drop-in replacements where possible)
- **Include defense-in-depth guidance** + regression tests/checks
## Resources
| Resource | Link |
|----------|------|
| Models | https://huggingface.co/collections/scthornton/securecode |
| Dataset | scthornton/securecode (2,185 examples) |
| Paper | https://arxiv.org/abs/2512.18542 |
## How to Test It
Copy and paste this prompt with your code:
## Dataset Coverage
SecureCode covers both traditional and emerging security domains:
- **Traditional web security** (OWASP Top 10 2021)
- **AI/ML security** (OWASP LLM Top 10 2025): prompt injection, RAG poisoning, model extraction, agentic AI patterns
## We Want Your Feedback
We're looking for real-world contributions:
- **Real snippets**: Share code that "slipped through review once" (sanitized is fine)
- **False positives/negatives**: What didn't work as expected?
- **CVE-grounded examples**: New vulnerability patterns you've encountered
**Please include**: language/framework + what the correct remediation looks like in your environment.
---
**Have contributions or suggestions?** I'd be happy to hear them. Thanks for your support!
**A collection of 8 code models (3B–20B) trained to behave like a security reviewer.**
## The Problem
Code assistants frequently recommend patterns that pass tests but fail security review—string-built SQL, brittle auth logic, unsafe parsing, insecure defaults, and more. I built SecureCode to address this gap.
## What SecureCode Does
- **Identify vulnerable patterns** and explain why they're risky
- **Outline plausible abuse paths** (defensive framing)
- **Propose secure rewrites** (drop-in replacements where possible)
- **Include defense-in-depth guidance** + regression tests/checks
## Resources
| Resource | Link |
|----------|------|
| Models | https://huggingface.co/collections/scthornton/securecode |
| Dataset | scthornton/securecode (2,185 examples) |
| Paper | https://arxiv.org/abs/2512.18542 |
## How to Test It
Copy and paste this prompt with your code:
You are a senior application security engineer. Review the code below.
Output:
(1) findings with severity,
(2) likely exploit scenarios (high level),
(3) secure rewrite,
(4) defense-in-depth recommendations,
(5) regression tests/checks.
Code: `...`## Dataset Coverage
SecureCode covers both traditional and emerging security domains:
- **Traditional web security** (OWASP Top 10 2021)
- **AI/ML security** (OWASP LLM Top 10 2025): prompt injection, RAG poisoning, model extraction, agentic AI patterns
## We Want Your Feedback
We're looking for real-world contributions:
- **Real snippets**: Share code that "slipped through review once" (sanitized is fine)
- **False positives/negatives**: What didn't work as expected?
- **CVE-grounded examples**: New vulnerability patterns you've encountered
**Please include**: language/framework + what the correct remediation looks like in your environment.
---
**Have contributions or suggestions?** I'd be happy to hear them. Thanks for your support!
reacted to
branikita's
post with 🔥
17 days ago
Post
2732
Robonine (Educational Robotics) completed a structural optimization of our 6-DOF robotic manipulator after a structural optimization study. By increasing structural rigidity through topology optimization and design refinement, we reduced end-effector deflection by over 60% (from ~1.05 mm to ~0.41 mm) and improved motion stability. The final configuration delivers higher precision and reliability for industrial applications.
Article: https://robonine.com/increasing-the-structural-rigidity-of-the-manipulator/
Article: https://robonine.com/increasing-the-structural-rigidity-of-the-manipulator/
- 5 replies
published
a
Space
17 days ago
posted
an
update
17 days ago
Post
230
Today, is a good day for me.
I have completed development of my QPU-1, the most powerful Quantum Processing Unit you can access through MCP (as far as I know and have tried).
Try it out for yourself using my mcp enabled space: lap-quantum/QPU-1-MCP
(And PS. This is my first MCP server, so give me suggestions if you want :D)
I have completed development of my QPU-1, the most powerful Quantum Processing Unit you can access through MCP (as far as I know and have tried).
Try it out for yourself using my mcp enabled space: lap-quantum/QPU-1-MCP
(And PS. This is my first MCP server, so give me suggestions if you want :D)
- 1 reply
liked
a
Space
18 days ago
published
a
Space
18 days ago
liked
a
model
18 days ago
really? didn't know it was a 500M$ mystery.
liked
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20 days ago