Feature Extraction
Transformers
Safetensors
English
llama
text-generation
text-embeddings-inference
compressed-tensors
Instructions to use chaymaemerhrioui/llamat-3-chat-awq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chaymaemerhrioui/llamat-3-chat-awq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="chaymaemerhrioui/llamat-3-chat-awq")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("chaymaemerhrioui/llamat-3-chat-awq") model = AutoModelForCausalLM.from_pretrained("chaymaemerhrioui/llamat-3-chat-awq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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library_name: transformers
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library_name: transformers
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license: mit
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language:
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- en
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base_model:
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- m3rg-iitd/llamat-3-chat
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pipeline_tag: feature-extraction
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# Model Card for Model ID
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