pipeline tools for testing

examples/pipeline.py

@@ -0,0 +1,32 @@
+import sys
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import transformers
+import torch
+
+model = "openaccess-ai-collective/minotaur-mpt-7b"
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    torch_dtype=torch.bfloat16,
+    trust_remote_code=True,
+    device_map="auto",
+)
+
+prompt = "".join([l for l in sys.stdin]).strip()
+
+sequences = pipeline(
+    prompt,
+    max_length=2048,
+    do_sample=True,
+    top_k=40,
+    top_p=0.95,
+    temperature=1.0,
+    num_beams=10,
+    num_return_sequences=1,
+    eos_token_id=tokenizer.eos_token_id,
+)
+for seq in sequences:
+    print(f"Result: {seq['generated_text']}")

examples/prompt.txt

@@ -0,0 +1,3 @@
+USER: your have 3 apples. you eat 2 pears. how many apples do you have left?
+
+ASSISTANT:

examples/prompt2.txt

@@ -0,0 +1,3 @@
+USER: What are 3 words that start with "ex" and end in "g"? What's the sum of 33 and 77?
+
+ASSISTANT: