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
Download generation_config.json from chaymaemerhrioui/llamat-3-chat-awq: direct link, hf CLI and curl.
- Browser
- Download file 111 Bytes
-
https://huggingface.co/chaymaemerhrioui/llamat-3-chat-awq/resolve/main/generation_config.json
- Command line
-
hf download hf://chaymaemerhrioui/llamat-3-chat-awq/generation_config.json
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curl -L -o generation_config.json https://huggingface.co/chaymaemerhrioui/llamat-3-chat-awq/resolve/main/generation_config.json
111 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "transformers_version": "4.57.6" | |
| } | |