clemsail commited on
Commit
0231213
·
verified ·
1 Parent(s): 7852897

chore: rebrand card to Ailiance

Browse files
Files changed (1) hide show
  1. README.md +11 -11
README.md CHANGED
@@ -6,7 +6,7 @@ tags:
6
  - peft
7
  - mlx
8
  - ailiance
9
- - eu-kiki
10
  - eu-ai-act
11
  - art-52
12
  - art-53
@@ -19,7 +19,7 @@ library_name: peft
19
 
20
  # devstral-cpp-lora
21
 
22
- LoRA adapter for **mistralai/Devstral-Small-2-24B-Instruct-2512**, part of the [ailiance](https://github.com/L-electron-Rare/ailiance) project. Live demo: https://www.ailiance.fr.
23
 
24
  > **EU AI Act compliance.** This card follows the **European Commission's
25
  > *Template for the Public Summary of Training Content* for general-purpose
@@ -37,7 +37,7 @@ LoRA adapter for **mistralai/Devstral-Small-2-24B-Instruct-2512**, part of the [
37
 
38
  | Field | Value |
39
  |---|---|
40
- | **Provider name and contact details** | L'Électron Rare (Saillant Clément) — `clemsail` on Hugging Face — Issues: https://github.com/L-electron-Rare/ailiance/issues |
41
  | **Authorised representative name and contact details** | Not applicable — provider is established within the European Union (France). |
42
 
43
  ## 1.2. Model identification
@@ -58,7 +58,7 @@ LoRA adapter for **mistralai/Devstral-Small-2-24B-Instruct-2512**, part of the [
58
  | **Approximate size in alternative units** | ≈ 0.6 M tokens (2 850 rows × ≈ 200 tokens/row). |
59
  | **Latest date of data acquisition / collection for model training** | 10/2025 (last commit on scraped repos). The model is **not** continuously trained on new data after this date. |
60
  | **Linguistic characteristics of the overall training data** | English (technical instruction language). No other natural languages. |
61
- | **Other relevant characteristics / additional comments** | LoRA fine-tune (rank 16, alpha 32, dropout 0.05); only attention projections (`q_proj`, `k_proj`, `v_proj`, `o_proj`) are trained. Per-record `_provenance` (source, SPDX licence, `record_idx`, `access_date`) attached at the system level (see [`docs/eu-ai-act-transparency.md`](https://github.com/L-electron-Rare/ailiance/blob/main/docs/eu-ai-act-transparency.md) §4.4). Tokenizer: inherited from the base model. |
62
 
63
  ---
64
 
@@ -142,8 +142,8 @@ _(N/A — no other data sources used.)_
142
 
143
  - **Public HF datasets (§2.1):** all carry permissive open licences (Apache-2.0, MIT, CC-BY-*, BSD); SPDX matrix verified per-source. The licences explicitly authorise instructional / model-training use for the rows actually selected.
144
  - **Web-scraped sources (§2.3):** prior to collection the provider verified `robots.txt`, `<meta name="robots" content="noai">`, `ai.txt`, and TDM-Reservation HTTP headers. Any source returning a reservation under Article 4(3) of Directive (EU) 2019/790 was excluded from collection. Scraping was limited to authoritative vendor-controlled repositories (ESP-IDF, STM32Cube, Arduino, KiCad symbols/footprints) operating under permissive licences.
145
- - **Vendor PDF datasheets (§2.2.2 where present):** processed under the EU DSM Directive Article 4 TDM exception. SHA-256 manifests and per-source legal-basis records are published in [`docs/pdf-compliance-report.md`](https://github.com/L-electron-Rare/ailiance/blob/main/docs/pdf-compliance-report.md).
146
- - **Public copyright policy (Art. 53(1)(c)):** [`docs/eu-ai-act-transparency.md`](https://github.com/L-electron-Rare/ailiance/blob/main/docs/eu-ai-act-transparency.md). Removal requests are handled via the issue tracker on the source repository; the provider commits to remove disputed content within 30 days and re-train on the next release cycle.
147
 
148
  ## 3.2. Removal of illegal content
149
 
@@ -167,8 +167,8 @@ _(N/A — no other data sources used.)_
167
  **HumanEval** (custom Studio scorer; EvalPlus extra-tests not run — Linux-only sandbox): base 87.20 → +cpp 85.98 = **−1.22 pts**. For rigorous HumanEval+ ��, sample re-scoring on Linux is required (samples preserved at `eval/results/2026-05-04/devstral-cpp-fused-humanevalplus/`).
168
 
169
  Full bench results, methodology, env.json, and rerun.sh per measurement:
170
- [`eval/results/SUMMARY.md`](https://github.com/L-electron-Rare/ailiance/blob/main/eval/results/SUMMARY.md) ·
171
- [`MODEL_CARD.md`](https://github.com/L-electron-Rare/ailiance/blob/main/MODEL_CARD.md).
172
 
173
  ---
174
 
@@ -211,11 +211,11 @@ python -m mlx_lm fuse \
211
  # Appendix D — Citation
212
 
213
  ```bibtex
214
- @misc{eu-kiki-2026,
215
- title = {eu-kiki: EU-sovereign multi-model LLM serving with HF-traceable LoRA adapters},
216
  author = {Saillant, Clément},
217
  year = {2026},
218
- url = {https://github.com/L-electron-Rare/ailiance},
219
  note = {Live demo: https://www.ailiance.fr}
220
  }
221
  ```
 
6
  - peft
7
  - mlx
8
  - ailiance
9
+ - ailiance
10
  - eu-ai-act
11
  - art-52
12
  - art-53
 
19
 
20
  # devstral-cpp-lora
21
 
22
+ LoRA adapter for **mistralai/Devstral-Small-2-24B-Instruct-2512**, part of the [ailiance](https://github.com/ailiance/ailiance) project. Live demo: https://www.ailiance.fr.
23
 
24
  > **EU AI Act compliance.** This card follows the **European Commission's
25
  > *Template for the Public Summary of Training Content* for general-purpose
 
37
 
38
  | Field | Value |
39
  |---|---|
40
+ | **Provider name and contact details** | Ailiance (Saillant Clément) — `clemsail` on Hugging Face — Issues: https://github.com/ailiance/ailiance/issues |
41
  | **Authorised representative name and contact details** | Not applicable — provider is established within the European Union (France). |
42
 
43
  ## 1.2. Model identification
 
58
  | **Approximate size in alternative units** | ≈ 0.6 M tokens (2 850 rows × ≈ 200 tokens/row). |
59
  | **Latest date of data acquisition / collection for model training** | 10/2025 (last commit on scraped repos). The model is **not** continuously trained on new data after this date. |
60
  | **Linguistic characteristics of the overall training data** | English (technical instruction language). No other natural languages. |
61
+ | **Other relevant characteristics / additional comments** | LoRA fine-tune (rank 16, alpha 32, dropout 0.05); only attention projections (`q_proj`, `k_proj`, `v_proj`, `o_proj`) are trained. Per-record `_provenance` (source, SPDX licence, `record_idx`, `access_date`) attached at the system level (see [`docs/eu-ai-act-transparency.md`](https://github.com/ailiance/ailiance/blob/main/docs/eu-ai-act-transparency.md) §4.4). Tokenizer: inherited from the base model. |
62
 
63
  ---
64
 
 
142
 
143
  - **Public HF datasets (§2.1):** all carry permissive open licences (Apache-2.0, MIT, CC-BY-*, BSD); SPDX matrix verified per-source. The licences explicitly authorise instructional / model-training use for the rows actually selected.
144
  - **Web-scraped sources (§2.3):** prior to collection the provider verified `robots.txt`, `<meta name="robots" content="noai">`, `ai.txt`, and TDM-Reservation HTTP headers. Any source returning a reservation under Article 4(3) of Directive (EU) 2019/790 was excluded from collection. Scraping was limited to authoritative vendor-controlled repositories (ESP-IDF, STM32Cube, Arduino, KiCad symbols/footprints) operating under permissive licences.
145
+ - **Vendor PDF datasheets (§2.2.2 where present):** processed under the EU DSM Directive Article 4 TDM exception. SHA-256 manifests and per-source legal-basis records are published in [`docs/pdf-compliance-report.md`](https://github.com/ailiance/ailiance/blob/main/docs/pdf-compliance-report.md).
146
+ - **Public copyright policy (Art. 53(1)(c)):** [`docs/eu-ai-act-transparency.md`](https://github.com/ailiance/ailiance/blob/main/docs/eu-ai-act-transparency.md). Removal requests are handled via the issue tracker on the source repository; the provider commits to remove disputed content within 30 days and re-train on the next release cycle.
147
 
148
  ## 3.2. Removal of illegal content
149
 
 
167
  **HumanEval** (custom Studio scorer; EvalPlus extra-tests not run — Linux-only sandbox): base 87.20 → +cpp 85.98 = **−1.22 pts**. For rigorous HumanEval+ ��, sample re-scoring on Linux is required (samples preserved at `eval/results/2026-05-04/devstral-cpp-fused-humanevalplus/`).
168
 
169
  Full bench results, methodology, env.json, and rerun.sh per measurement:
170
+ [`eval/results/SUMMARY.md`](https://github.com/ailiance/ailiance/blob/main/eval/results/SUMMARY.md) ·
171
+ [`MODEL_CARD.md`](https://github.com/ailiance/ailiance/blob/main/MODEL_CARD.md).
172
 
173
  ---
174
 
 
211
  # Appendix D — Citation
212
 
213
  ```bibtex
214
+ @misc{ailiance-2026,
215
+ title = {ailiance: EU-sovereign multi-model LLM serving with HF-traceable LoRA adapters},
216
  author = {Saillant, Clément},
217
  year = {2026},
218
+ url = {https://github.com/ailiance/ailiance},
219
  note = {Live demo: https://www.ailiance.fr}
220
  }
221
  ```