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Runtime error
| import torch | |
| import torch.nn.functional as F | |
| import transformers | |
| import gradio as gr | |
| from src.client import DistributedBloomForCausalLM | |
| INITIAL_PEERS = [ | |
| '/ip4/193.106.95.184/tcp/31337/p2p/QmUigSxrVz9x5FR9ZYr4iRfEX2vDxihL2YZtDd7sp2eKnM', | |
| '/ip6/193.106.95.184/tcp/21337/p2p/QmSXDXLeSMXjS4YerDrdn1zpGQaNzkZ9ogN2SoAEyAdDhs', | |
| '/ip6/193.106.95.184/udp/21337/quic/QmSXDXLeSMXjS4YerDrdn1zpGQaNzkZ9ogN2SoAEyAdDhs', | |
| ] | |
| tokenizer = transformers.BloomTokenizerFast.from_pretrained("bigscience/test-bloomd-6b3") | |
| model = DistributedBloomForCausalLM.from_pretrained("bigscience/test-bloomd-6b3", initial_peers=INITIAL_PEERS, low_cpu_mem_usage=True, torch_dtype=torch.float32) | |
| def inference(text, seq_length=1): | |
| input_ids = tokenizer(text, return_tensors='pt')['input_ids'] | |
| with torch.inference_mode(), model.transformer.h.inference_session() as remote_transformer: | |
| for i in range(seq_length): | |
| h = model.transformer.word_embeddings(input_ids) | |
| h = model.transformer.word_embeddings_layernorm(h) | |
| h = remote_transformer.step(h) # note [yozh]: this line currently freezes for 10 seconds first time only, its gonna be fixed in the nearest PR | |
| h = model.transformer.ln_f(h) | |
| h = F.linear(h, weight=model.transformer.word_embeddings.weight) # note: this line takes a while, will also be fixed | |
| next_token_ix = torch.multinomial((h[0, -1] / 0.8).softmax(-1), 1) | |
| # print(end=tokenizer.decode(next_token_ix.item())) | |
| input_ids = next_token_ix.view(1, 1) | |
| return tokenizer.decode(input_ids.item()) | |
| iface = gr.Interface(fn=inference, inputs="text", outputs="text") | |
| iface.launch() |