Instructions to use zai-org/chatglm3-6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zai-org/chatglm3-6b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zai-org/chatglm3-6b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Yuxuan Zhang commited on
add set_input_embeddings(self, value):
Browse files- modeling_chatglm.py +3 -0
modeling_chatglm.py
CHANGED
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@@ -769,6 +769,9 @@ class ChatGLMModel(ChatGLMPreTrainedModel):
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def get_input_embeddings(self):
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return self.embedding.word_embeddings
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def get_prompt(self, batch_size, device, dtype=torch.half):
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prefix_tokens = self.prefix_tokens.unsqueeze(0).expand(batch_size, -1).to(device)
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past_key_values = self.prefix_encoder(prefix_tokens).type(dtype)
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def get_input_embeddings(self):
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return self.embedding.word_embeddings
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def set_input_embeddings(self, value):
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self.embedding.word_embeddings = value
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def get_prompt(self, batch_size, device, dtype=torch.half):
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prefix_tokens = self.prefix_tokens.unsqueeze(0).expand(batch_size, -1).to(device)
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past_key_values = self.prefix_encoder(prefix_tokens).type(dtype)
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