Text Generation
PEFT
Safetensors
English
lora
apertus
optical-networks
intent-based-networking
hack-apertus
conversational
Instructions to use blackfish021/apertus-lightpath-lora-v2-e2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use blackfish021/apertus-lightpath-lora-v2-e2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("andreasmartin/apertus-v1.5-8b-text") model = PeftModel.from_pretrained(base_model, "blackfish021/apertus-lightpath-lora-v2-e2") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from blackfish021/apertus-lightpath-lora-v2-e2: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/blackfish021/apertus-lightpath-lora-v2-e2/resolve/main/tokenizer.json
- Command line
-
hf download hf://blackfish021/apertus-lightpath-lora-v2-e2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/blackfish021/apertus-lightpath-lora-v2-e2/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- eb426b0e09c283e4e9241d384d2b5d7d49132d0ba463e736c9e0b65be0d2317e
- Size of remote file:
- 17.1 MB
- SHA256:
- fe44788cabee7aed84a76bdfe7e17397f311c40fcecaad16d52a074999d6c11c
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