Create README.md

README.md

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+ Experimental 20B instruction tuned model based on gpt-neox-20b.
+```
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+name = "jordiclive/instruction-tuned-gpt-neox-20b"
+model = AutoModelForCausalLM.from_pretrained(name, device_map=chip_map, torch_dtype=torch.float16)# load_in_8bit=True )
+tokenizer = AutoTokenizer.from_pretrained(name)
+
+def generate_from_model(model, tokenizer):
+    encoded_input = tokenizer(text, return_tensors='pt')
+    output_sequences = model.generate(
+                                    input_ids=encoded_input['input_ids'].cuda(0),
+                                    do_sample=True,
+                                    max_new_tokens=35,
+                                    num_return_sequences=1,
+                                    top_p=0.95,
+                                    temperature=0.5,
+                                    penalty_alpha=0.6,
+                                    top_k=4,
+                                    output_scores=True,
+                                    return_dict_in_generate=True,
+                                    repetition_penalty=1.03,
+                                    eos_token_id=0,
+                                    use_cache=True
+                                  )
+    gen_sequences = output_sequences.sequences[:, encoded_input['input_ids'].shape[-1]:]
+    for sequence in gen_sequences:
+        new_line=tokenizer.decode(sequence, skip_special_tokens=True)
+        print(new_line)
+
+text = "User: Will big tech A.I be adulterated with advertisement?\n\nOA:"
+generate_from_model(model,tokenizer)
+```