Text Generation
Transformers
Safetensors
llama
conversational
text-generation-inference
Inference Endpoints
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---
library_name: transformers
license: llama3
datasets:
- aqua_rat
- microsoft/orca-math-word-problems-200k
- m-a-p/CodeFeedback-Filtered-Instruction
---

# Guido-Llama-3-70B-Instruct-32K

### Built with Meta Llama 3

This is a 32K version of Llama-3-70B-Instruct.

More details are coming soon.

### Model Description

- **Developed by:** [Guido AI](https://guido-marsch.com)
- **License:** https://llama.meta.com/llama3/license/
- **Finetuned from model:** [meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct).

## How to use

The prompt format is unchanged from Llama 3 70B Instruct.

### Use with transformers

See the snippet below for usage with Transformers:

```python
import transformers
import torch

model_id = "EditorZ/Guido-Llama-3-70B-Instruct"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

messages = [
    {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
    {"role": "user", "content": "Who are you?"},
]

prompt = pipeline.tokenizer.apply_chat_template(
		messages, 
		tokenize=False, 
		add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=256,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.6,
    top_p=0.9,
)
print(outputs[0]["generated_text"][len(prompt):])
```