What do we download when we download a large model from HuggingFace?
Explore the secrets behind the download of the HuggingFace large model and gain an in-depth understanding of the model file structure and function.
Core content:
1. The role and composition of model weights and configuration files
2. Tokenizer-related files and their importance
3. Reasoning and generation configuration and model documentation license information
In today's era of rapid development of large models,HuggingFace It has become an important platform that AI researchers and developers cannot avoid.
It not only has a variety of open source large models, but also rich data sets, which greatly facilitates everyone's AI research and application.
When we from HuggingFace When you download a model, you will find that it contains multiple files. These files have their own functions to ensure that the model can run properly. So, what are the specific functions of these files? This article will take a look.
1. Model weights and configuration files
model-xxxx-of-yyyy.safetensors : This is the core file that stores the weight parameters of the model after training. Large models usually consist of multiple such files, and their size is often the largest. config.json : This file defines the structural information of the model, such as the number of layers, hidden layer size, activation function, etc. It is the key to correctly loading the model. model.safetensors.index.json : This file describes the correspondence between each layer of the model and the weight file, ensuring that the model can correctly find the required weight data when loading.
2. Tokenizer related files
tokenizer.json : Complete tokenizer definition, including encoding rules for each token. tokenizer_config.json : used to store additional configuration information of the tokenizer, such as special tokens (such as [CLS], [SEP]), chat templates, truncation methods, filling rules, etc. merges.txt (applicable to BPE tokenizer): defines the token merging rules based on the BPE (Byte Pair Encoding) method. vocab.txt (applicable to BERT-type models): stores the vocabulary of the model, and each token has a corresponding ID.
3. Reasoning and Generation Configuration
generation_config.json : This file defines the default parameters of the model during inference or text generation, such as temperature, top-k, top-p, repetition penalty, etc. These parameters will directly affect the generation effect.
4. Documentation and License Information
README.md : The model's readme file, which introduces the model's training method, usage, and applicable scenarios. LICENSE : The license agreement of the model, which specifies the usage restrictions and authorization methods of the model.
Summarize
When we download a large model from Hugging Face, we actually get a complete "ecosystem" that includes model weights , configuration files , tokenizer information , and parameter settings required for inference , etc. These files work together to enable the model to run smoothly and produce expected results.
