Text Classification
Transformers
Safetensors
English
qwen3_5_text
text-generation
system-one
system-two
blocks-of-experts
typed-decisions
decision-model
calibrated-probabilities
knowledge-distillation
jev
noul
choice
score
lora
qwen3_5
dual-head
vllm
multimodal
vision
computer-use
robotics
Eval Results (legacy)
Instructions to use autotrust/JEV-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autotrust/JEV-9B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="autotrust/JEV-9B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("autotrust/JEV-9B") model = AutoModelForCausalLM.from_pretrained("autotrust/JEV-9B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download reports/vl/microlens.json from autotrust/JEV-9B: direct link, hf CLI and curl.
- Browser
- Download file 1.13 kB
-
https://huggingface.co/autotrust/JEV-9B/resolve/main/reports/vl/microlens.json
- Command line
-
hf download hf://autotrust/JEV-9B/reports/vl/microlens.json
-
curl -L -o microlens.json https://huggingface.co/autotrust/JEV-9B/resolve/main/reports/vl/microlens.json
1.13 kB
| { | |
| "metrics": { | |
| "random": [ | |
| 0.48894736842105274, | |
| 0.04, | |
| 0.205, | |
| 0.21949352013581572, | |
| 0.16814529929564767 | |
| ], | |
| "pop": [ | |
| 0.5047368421052628, | |
| 0.04, | |
| 0.23, | |
| 0.2040320275478807, | |
| 0.16545971297364492 | |
| ], | |
| "title_sim": [ | |
| 0.6015789473684214, | |
| 0.205, | |
| 0.385, | |
| 0.3667476255083533, | |
| 0.32769800815369743 | |
| ], | |
| "jev_titles": [ | |
| 0.6171052631578946, | |
| 0.155, | |
| 0.425, | |
| 0.36171880061708434, | |
| 0.3013690903180073 | |
| ], | |
| "jev_images": [ | |
| 0.7210526315789467, | |
| 0.255, | |
| 0.6, | |
| 0.48104892350240086, | |
| 0.4064158857783086 | |
| ], | |
| "jev_both": [ | |
| 0.7149999999999997, | |
| 0.245, | |
| 0.54, | |
| 0.47049149692806513, | |
| 0.3986715261862323 | |
| ], | |
| "itemcf": [ | |
| 0.727631578947368, | |
| 0.355, | |
| 0.49, | |
| 0.5031604435662497, | |
| 0.4600847555222559 | |
| ] | |
| }, | |
| "bootstrap_auc": { | |
| "jev_images-jev_titles": [ | |
| 0.10394736842105262, | |
| 0.05315789473684209, | |
| 0.15473684210526314 | |
| ], | |
| "jev_images-title_sim": [ | |
| 0.1194736842105263, | |
| 0.06789473684210526, | |
| 0.1694736842105263 | |
| ], | |
| "jev_images-itemcf": [ | |
| -0.0065789473684210575, | |
| -0.048947368421052635, | |
| 0.035789473684210524 | |
| ] | |
| }, | |
| "n_users": 200 | |
| } |