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Lora-Meta-Llama2-7b-chat-hf-QandA_2g_v01-v05
daochf/Lora-Meta-Llama2-7b-chat-hf-QandA_2g_v01-v05
Lora-Meta-Llama2-7b-chat-hf-QandA_2g_v01-v05 is a machine learning model from daochf. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft.
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At a glance
- Library
- peft
- Access
- Public
- Created
- Jan 9, 2024
- Updated
- Jan 9, 2024
- SHA
- f1cb0f92
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From the Hugging Face model README
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<!-- Provide a quick summary of what the model is/does. -->Start training at: 2024-01-08 08:10:15.228841
0%| | 0/80440 [00:00<?, ?it/s]You're using a LlamaTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
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100%|█████████████| 80440/80440 [6:40:34<00:00, 3.35it/s]
Training done at: 2024-01-08 14:50:49.566594
For Model: meta-llama/Llama-2-7b-hf
In Adapter: Lora-Meta-Llama2-7b-chat-hf-QandA_2g_v01-v05
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Model Details
Model Description
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Uses
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Out-of-Scope Use
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Recommendations
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How to Get Started with the Model
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Training Details
Training Data
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Training Procedure
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Training Hyperparameters
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Evaluation
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Summary
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Environmental Impact
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Training procedure
The following bitsandbytes quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: float16
Framework versions
- PEFT 0.6.2
- Library
- peft
- Created
- Jan 9, 2024
- Updated
- Jan 9, 2024