SmolLM2-CoT-360M-GGUF

59
9
llama
by
prithivMLmods
Language Model
OTHER
New
59 downloads
Early-stage
Try on Hugging FaceAdd to Compare
Edge AI:
Mobile
Laptop
Server
Unknown
Mobile
Laptop
Server
Quick Summary

AI model with specialized capabilities.

Code Examples

python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
model, tokenizer = setup_chat_format(model=model, tokenizer=tokenizer)
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))
python
prompt = "Explain AGI ?"
   pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
   print(pipe(prompt, max_new_tokens=200))

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