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Browse files- 1d1fb4601504338d2839f62b643cad8e7db1b9d6bb5dc95e78b7e50b97e8a88d (695e76232319ee0e5ef5214e66872393111ac6c9)
- README.md +4 -3
- config.json +2 -2
- plots.png +0 -0
- smash_config.json +1 -1
README.md
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---
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library_name: pruna-engine
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thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
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metrics:
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- memory_disk
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- inference_throughput
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- inference_CO2_emissions
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- inference_energy_consumption
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---
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<!-- header start -->
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<!-- 200823 -->
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## Results
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**Frequently Asked Questions**
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- ***How does the compression work?*** The model is compressed with llm-int8.
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("PrunaAI/ai-forever-rugpt3large_based_on_gpt2-bnb-8bit-smashed",
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trust_remote_code=True)
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tokenizer = AutoTokenizer.from_pretrained("ai-forever/rugpt3large_based_on_gpt2")
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input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]
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---
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thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
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metrics:
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- memory_disk
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- inference_throughput
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- inference_CO2_emissions
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- inference_energy_consumption
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tags:
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- pruna-ai
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---
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<!-- header start -->
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<!-- 200823 -->
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## Results
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![image info](./plots.png)
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**Frequently Asked Questions**
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- ***How does the compression work?*** The model is compressed with llm-int8.
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("PrunaAI/ai-forever-rugpt3large_based_on_gpt2-bnb-8bit-smashed",
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trust_remote_code=True, device_map='auto')
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tokenizer = AutoTokenizer.from_pretrained("ai-forever/rugpt3large_based_on_gpt2")
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input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]
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config.json
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{
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"_name_or_path": "/tmp/
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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"quantization_config": {
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"bnb_4bit_compute_dtype": "bfloat16",
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"bnb_4bit_quant_type": "fp4",
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"bnb_4bit_use_double_quant":
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"llm_int8_enable_fp32_cpu_offload": false,
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"llm_int8_has_fp16_weight": false,
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"llm_int8_skip_modules": [
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{
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"_name_or_path": "/tmp/tmpcq0ubzft",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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"quantization_config": {
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"bnb_4bit_compute_dtype": "bfloat16",
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"bnb_4bit_quant_type": "fp4",
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"bnb_4bit_use_double_quant": false,
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"llm_int8_enable_fp32_cpu_offload": false,
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"llm_int8_has_fp16_weight": false,
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"llm_int8_skip_modules": [
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plots.png
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smash_config.json
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"compilers": "None",
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"task": "text_text_generation",
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"device": "cuda",
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"cache_dir": "/ceph/hdd/staff/charpent/.cache/
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"batch_size": 1,
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"model_name": "ai-forever/rugpt3large_based_on_gpt2",
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"pruning_ratio": 0.0,
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"compilers": "None",
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"task": "text_text_generation",
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"device": "cuda",
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"cache_dir": "/ceph/hdd/staff/charpent/.cache/models2w6zq7n4",
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"batch_size": 1,
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"model_name": "ai-forever/rugpt3large_based_on_gpt2",
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"pruning_ratio": 0.0,
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