Instructions to use cfli/minicpm_tokencompress_compensate_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cfli/minicpm_tokencompress_compensate_test with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openbmb/MiniCPM-2B-dpo-fp32") model = PeftModel.from_pretrained(base_model, "cfli/minicpm_tokencompress_compensate_test") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from cfli/minicpm_tokencompress_compensate_test: direct link, hf CLI and curl.
- Browser
- Download file 1.99 MB
-
https://huggingface.co/cfli/minicpm_tokencompress_compensate_test/resolve/main/tokenizer.model
- Command line
-
hf download hf://cfli/minicpm_tokencompress_compensate_test/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/cfli/minicpm_tokencompress_compensate_test/resolve/main/tokenizer.model
1.99 MB
- Xet hash:
- a03eac1c5cec56ddeed568992f4a70a6120336d6cff09142e9d717122a4a391e
- Size of remote file:
- 1.99 MB
- SHA256:
- c9aafcd7da1f5611dab6be545db74d5552a2ccc9c2a12c72ea7be63aac4a25d7
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