Instructions to use Bearnardd/test_bearnard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bearnardd/test_bearnard with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Bearnardd/test_bearnard") model = AutoModelForCausalLM.from_pretrained("Bearnardd/test_bearnard") - 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="Bearnardd//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("Bearnardd//tmp/
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model = AutoModelForCausalLMWithValueHead.from_pretrained("Bearnardd//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="Bearnardd//tmp/tmpcs5od8jz/Bearnardd/test_bearnard")
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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("Bearnardd//tmp/tmpcs5od8jz/Bearnardd/test_bearnard")
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model = AutoModelForCausalLMWithValueHead.from_pretrained("Bearnardd//tmp/tmpcs5od8jz/Bearnardd/test_bearnard")
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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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