Text Classification
Transformers
Safetensors
English
Chinese
internlm2
feature-extraction
reward model
custom_code
4-bit precision
bitsandbytes
Instructions to use SteveTran/internlm2-20b-4bit-RM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SteveTran/internlm2-20b-4bit-RM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SteveTran/internlm2-20b-4bit-RM", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SteveTran/internlm2-20b-4bit-RM", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from SteveTran/internlm2-20b-4bit-RM: direct link, hf CLI and curl.
- Browser
- Download file 5.75 MB
-
https://huggingface.co/SteveTran/internlm2-20b-4bit-RM/resolve/main/tokenizer.json
- Command line
-
hf download hf://SteveTran/internlm2-20b-4bit-RM/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/SteveTran/internlm2-20b-4bit-RM/resolve/main/tokenizer.json
5.75 MB
File too large to display, you can check the raw version instead.