Text Classification
Transformers
Safetensors
English
Chinese
gemma4
image-text-to-text
decision-model
system-one
decision-index
lora-merged
Instructions to use PelaAI/KnowLine-31B-Gen1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PelaAI/KnowLine-31B-Gen1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PelaAI/KnowLine-31B-Gen1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("PelaAI/KnowLine-31B-Gen1") model = AutoModelForMultimodalLM.from_pretrained("PelaAI/KnowLine-31B-Gen1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download SHA256SUMS from PelaAI/KnowLine-31B-Gen1: direct link, hf CLI and curl.
- Browser
- Download file 2.62 kB
-
https://huggingface.co/PelaAI/KnowLine-31B-Gen1/resolve/main/SHA256SUMS
- Command line
-
hf download hf://PelaAI/KnowLine-31B-Gen1/SHA256SUMS
-
curl -L -o SHA256SUMS https://huggingface.co/PelaAI/KnowLine-31B-Gen1/resolve/main/SHA256SUMS
2.62 kB
| 746250e07bbd3df48d42f0bf6c0a9226ca047f312c6cdc8a2c7124971d228219 INFERENCE.md | |
| 50cbab8a892c5f2993b8c7351a99182507472def3b1374558308605d99b86b32 LICENSE | |
| 348d4666c951cc4cf193ee1b3130becb0c93d4d5bfe520031a97d5139d0f0bb6 README.md | |
| a062559575c04c743ad074fa629ba87d571db27d2f50d50d2334734170262447 README.zh.md | |
| 94899c0f917d93f6fe81c95744d1e8ddab2d21d39228d2e4aec1fb2a25bff413 chat_template.jinja | |
| 086d159de6603dd83bf2c457acabd7d950bbda809a8ca1730ca3de490757daa0 config.json | |
| d4226bbe3117d2d253ba4609720ba82c6c4ce4627a9a6ae05387c78983ac03de generation_config.json | |
| 4f05e06b6021e6b0b5f00d4c6bc2f98a3a824c9a254ec901ba42c9070ac50ac9 knowline_engine.py | |
| 2e839fa24f1ad9c980898b2a9aa62e2154ba3f57618bd5f2fedb5756f61f062f knowline_layout.py | |
| 13ca50c4001fac0aa3899a35ff01e60f311132c571b17a8c3dc7aa6001ad2f3f knowline_server.py | |
| 48afa2da8b157757ded61e96a36388f03f98a4322881cfd783f48c587764caa5 model-00001-of-00013.safetensors | |
| 695ebe74c272f621b193fbacd1c4543f82b930a6a5d62b39ef3967d784765471 model-00002-of-00013.safetensors | |
| df06de1500545397945cdcdb117a4ea17100efac6b005ad804adbb39edbb0247 model-00003-of-00013.safetensors | |
| 9181dfafc3931c9f6b0f95dba66a063f450021c00b3ef03f05d74f3254c1a49b model-00004-of-00013.safetensors | |
| 5598d7618c2bb7a15c12a98e394ec5eeba8ad0bd40db163450e0490508fdf7ab model-00005-of-00013.safetensors | |
| 7138ea4a2cfd8192d9a125bdbe4d10d23a1995188a17a8d9e2b6bb3c4ba09461 model-00006-of-00013.safetensors | |
| c63426e8dbb87ccb7ebfa73e4192f2c60333165119ead0aa4f7f57ae1bc4dec9 model-00007-of-00013.safetensors | |
| f6b9d174cd0c68df7d8c0c1299e61844ab280f0be45cb936652dbc127797b50a model-00008-of-00013.safetensors | |
| ad46173df24c2fd4e2fa2b2300529b472480c8e5bc2cb9f771a90ec8361bcfae model-00009-of-00013.safetensors | |
| 0a23037d64e5c6da1545a2c1ff64727cb6748df36420cd7311f75170ce910674 model-00010-of-00013.safetensors | |
| 905aaf0ccec3974dae536bb884b7db82c3bb8712104e99a80de1e77a474a5aa9 model-00011-of-00013.safetensors | |
| 1d31e54ac8c9e9812cbfac1f6df738a3d5cb69e578b84a403e3f2ffa1da10252 model-00012-of-00013.safetensors | |
| 8c2ef92b1e901d2378ba07eb91729d6334d4fb9cf480d0883ad918d8f3c811bf model-00013-of-00013.safetensors | |
| 9b5fc8ba7e42645edd2bf6dca007859b5dd31f1bbee2e64ae261521463644eb2 model.safetensors.index.json | |
| 32bdf45d2ad4cc29a0822ddd157a182de76644f0419a6228d151495256e9813c processor_config.json | |
| 166cbef96c8cffe5a812138c119ec12d6589c7f619289682e45cce0063a9169d serve_knowline.sh | |
| 463a46c5ea253649bd5f43809655637d2d41939e503c81ddd01b28355d736f62 temperatures.json | |
| cc8d3a0ce36466ccc1278bf987df5f71db1719b9ca6b4118264f45cb627bfe0f tokenizer.json | |
| 90c3a3ba5bf53818383a58e1a776cbcacd2a038d4812eaa373e1522f2d06f3df tokenizer_config.json | |