Instructions to use jatshi/StreamSense-Serve-v4-Router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jatshi/StreamSense-Serve-v4-Router with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jatshi/StreamSense-Serve-v4-Router") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Download e2e_diagnostics.json from jatshi/StreamSense-Serve-v4-Router: direct link, hf CLI and curl.
- Browser
- Download file 2.74 kB
-
https://huggingface.co/jatshi/StreamSense-Serve-v4-Router/resolve/main/e2e_diagnostics.json
- Command line
-
hf download hf://jatshi/StreamSense-Serve-v4-Router/e2e_diagnostics.json
-
curl -L -o e2e_diagnostics.json https://huggingface.co/jatshi/StreamSense-Serve-v4-Router/resolve/main/e2e_diagnostics.json
2.74 kB
| { | |
| "schema_version": 1, | |
| "bootstrap_unit": "group_id", | |
| "bootstrap_iterations": 10000, | |
| "independent_groups": 8, | |
| "systems": { | |
| "always_vlm": { | |
| "cases": 32, | |
| "quality_pass_rate": 0.6875, | |
| "group_bootstrap_95_ci": [ | |
| 0.46875, | |
| 0.875 | |
| ], | |
| "failure_counts": { | |
| "state": 9, | |
| "answer_fact": 1, | |
| "citation": 4 | |
| }, | |
| "per_group_quality_pass_rate": { | |
| "meeting-conflict-003": 0.75, | |
| "meeting-conflict-005": 0.25, | |
| "meeting-normal-001": 1.0, | |
| "meeting-visual-001": 1.0, | |
| "meeting-visual-008": 1.0, | |
| "safety-risk-003": 0.25, | |
| "safety-risk-004": 0.5, | |
| "support-normal-001": 0.75 | |
| } | |
| }, | |
| "learned": { | |
| "cases": 32, | |
| "quality_pass_rate": 0.65625, | |
| "group_bootstrap_95_ci": [ | |
| 0.40625, | |
| 0.875 | |
| ], | |
| "failure_counts": { | |
| "state": 10, | |
| "answer_fact": 1, | |
| "citation": 5 | |
| }, | |
| "per_group_quality_pass_rate": { | |
| "meeting-conflict-003": 0.75, | |
| "meeting-conflict-005": 0.0, | |
| "meeting-normal-001": 1.0, | |
| "meeting-visual-001": 1.0, | |
| "meeting-visual-008": 1.0, | |
| "safety-risk-003": 0.25, | |
| "safety-risk-004": 0.5, | |
| "support-normal-001": 0.75 | |
| } | |
| }, | |
| "never_vlm": { | |
| "cases": 32, | |
| "quality_pass_rate": 0.78125, | |
| "group_bootstrap_95_ci": [ | |
| 0.53125, | |
| 0.96875 | |
| ], | |
| "failure_counts": { | |
| "state": 6, | |
| "answer_fact": 1, | |
| "citation": 5 | |
| }, | |
| "per_group_quality_pass_rate": { | |
| "meeting-conflict-003": 0.75, | |
| "meeting-conflict-005": 0.0, | |
| "meeting-normal-001": 1.0, | |
| "meeting-visual-001": 1.0, | |
| "meeting-visual-008": 1.0, | |
| "safety-risk-003": 0.75, | |
| "safety-risk-004": 1.0, | |
| "support-normal-001": 0.75 | |
| } | |
| } | |
| }, | |
| "paired_quality": { | |
| "always_vlm_minus_learned": { | |
| "paired_cases": 32, | |
| "quality_rate_delta": 0.03125, | |
| "group_bootstrap_95_ci": [ | |
| 0.0, | |
| 0.09375 | |
| ], | |
| "both_pass": 21, | |
| "left_only_pass": 1, | |
| "right_only_pass": 0, | |
| "both_fail": 10 | |
| }, | |
| "always_vlm_minus_never_vlm": { | |
| "paired_cases": 32, | |
| "quality_rate_delta": -0.09375, | |
| "group_bootstrap_95_ci": [ | |
| -0.25, | |
| 0.0625 | |
| ], | |
| "both_pass": 21, | |
| "left_only_pass": 1, | |
| "right_only_pass": 4, | |
| "both_fail": 6 | |
| }, | |
| "learned_minus_never_vlm": { | |
| "paired_cases": 32, | |
| "quality_rate_delta": -0.125, | |
| "group_bootstrap_95_ci": [ | |
| -0.3125, | |
| 0.0 | |
| ], | |
| "both_pass": 21, | |
| "left_only_pass": 0, | |
| "right_only_pass": 4, | |
| "both_fail": 7 | |
| } | |
| } | |
| } |