Instructions to use internlm/internlm-xcomposer2d5-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use internlm/internlm-xcomposer2d5-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="internlm/internlm-xcomposer2d5-7b")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("internlm/internlm-xcomposer2d5-7b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update modeling_internlm_xcomposer2.py
#13
by yuhangzang - opened
modeling_internlm_xcomposer2.py
CHANGED
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@@ -421,7 +421,7 @@ class InternLMXComposer2ForCausalLM(InternLM2PreTrainedModel):
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image, text)
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else:
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to_regress_tokens, targets = self.text2emb(
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-
text,
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to_regress_embeds = self.model.tok_embeddings(
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to_regress_tokens.input_ids)
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attention_mask = to_regress_tokens.attention_mask
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image, text)
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else:
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to_regress_tokens, targets = self.text2emb(
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+
text, add_special_tokens=True)
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to_regress_embeds = self.model.tok_embeddings(
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to_regress_tokens.input_ids)
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attention_mask = to_regress_tokens.attention_mask
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