KoGPT2-FineTuning
KoGPT2-FineTuning copied to clipboard
Bump transformers from 4.36.0 to 4.38.0
Bumps transformers from 4.36.0 to 4.38.0.
Release notes
Sourced from transformers's releases.
v4.38: Gemma, Depth Anything, Stable LM; Static Cache, HF Quantizer, AQLM
New model additions
💎 Gemma 💎
Gemma is a new opensource Language Model series from Google AI that comes with a 2B and 7B variant. The release comes with the pre-trained and instruction fine-tuned versions and you can use them via
AutoModelForCausalLM
,GemmaForCausalLM
orpipeline
interface!Read more about it in the Gemma release blogpost: https://hf.co/blog/gemma
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b") model = AutoModelForCausalLM.from_pretrained("google/gemma-2b", device_map="auto", torch_dtype=torch.float16)
input_text = "Write me a poem about Machine Learning." input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
outputs = model.generate(**input_ids)
You can use the model with Flash Attention, SDPA, Static cache and quantization API for further optimizations !
- Flash Attention 2
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")
model = AutoModelForCausalLM.from_pretrained( "google/gemma-2b", device_map="auto", torch_dtype=torch.float16, attn_implementation="flash_attention_2" )
input_text = "Write me a poem about Machine Learning." input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
outputs = model.generate(**input_ids)
- bitsandbytes-4bit
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")
model = AutoModelForCausalLM.from_pretrained( "google/gemma-2b", device_map="auto", load_in_4bit=True ) </tr></table>
... (truncated)
Commits
08ab54a
[gemma
] Adds support for Gemma 💎 (#29167)2de9314
[Maskformer
] safely get backbone config (#29166)476957b
🚨 Llama: update rope scaling to match static cache changes (#29143)7a4bec6
Release: 4.38.0ee3af60
Add support for fine-tuning CLIP-like models using contrastive-image-text exa...0996a10
Revert low cpu mem tie weights (#29135)15cfe38
[Core tokenization
]add_dummy_prefix_space
option to help with latest is...efdd436
FIX [PEFT
/Trainer
] Handle better peft + quantized compiled models (#29...5e95dca
[cuda kernels
] only compile them when initializing (#29133)a7755d2
Generate: unset GenerationConfig parameters do not raise warning (#29119)- Additional commits viewable in compare view
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