Instructions to use eurus7/working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eurus7/working with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("eurus7/working", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Push model using huggingface_hub.
Browse files
README.md
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@@ -24,7 +24,7 @@ You can then generate text as follows:
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```python
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from transformers import pipeline
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generator = pipeline("text-generation", model="eurus7//tmp/
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outputs = generator("Hello, my llama is cute")
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```
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from transformers import AutoTokenizer
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from trl import AutoModelForCausalLMWithValueHead
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tokenizer = AutoTokenizer.from_pretrained("eurus7//tmp/
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model = AutoModelForCausalLMWithValueHead.from_pretrained("eurus7//tmp/
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inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
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outputs = model(**inputs, labels=inputs["input_ids"])
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```python
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from transformers import pipeline
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generator = pipeline("text-generation", model="eurus7//tmp/tmpwwzutik5/eurus7/working")
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outputs = generator("Hello, my llama is cute")
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```
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from transformers import AutoTokenizer
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from trl import AutoModelForCausalLMWithValueHead
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tokenizer = AutoTokenizer.from_pretrained("eurus7//tmp/tmpwwzutik5/eurus7/working")
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model = AutoModelForCausalLMWithValueHead.from_pretrained("eurus7//tmp/tmpwwzutik5/eurus7/working")
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inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
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outputs = model(**inputs, labels=inputs["input_ids"])
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