Felladrin / llama family / text-generation
Llama-160M-Chat-v1
Felladrin/Llama-160M-Chat-v1
Benchmarks
Where it scores.
General Provisional —
Coding Provisional —
Math Provisional —
Reasoning Provisional —
Normalized 0–100 across indexed models.
Runnable variants
Pick a size.
| Precision | Format | Size | Params | File |
|---|---|---|---|---|
| FP16 / smallest | SAFETENSORS | 650 MB | — | model.safetensors |
Sizes are file sizes, not peak runtime memory.
From the Hugging Face model card
About this model.
From the Hugging Face model card
About this model.
A Llama Chat Model of 160M Parameters
- Base model: JackFram/llama-160m
- Datasets:
- Availability in other ML formats:
Recommended Prompt Format
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{user_message}<|im_end|>
<|im_start|>assistant
Recommended Inference Parameters
penalty_alpha: 0.5
top_k: 4
repetition_penalty: 1.01
Usage Example
from transformers import pipeline
generate = pipeline("text-generation", "Felladrin/Llama-160M-Chat-v1")
messages = [
{
"role": "system",
"content": "You are a helpful assistant who answers user's questions with details and curiosity.",
},
{
"role": "user",
"content": "What are some potential applications for quantum computing?",
},
]
prompt = generate.tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
output = generate(
prompt,
max_new_tokens=1024,
penalty_alpha=0.5,
top_k=4,
repetition_penalty=1.01,
)
print(output[0]["generated_text"])
Old Open LLM Leaderboard Evaluation Results
| Metric | Value |
|---|---|
| Avg. | 30.27 |
| AI2 Reasoning Challenge (25-Shot) | 24.74 |
| HellaSwag (10-Shot) | 35.29 |
| MMLU (5-Shot) | 26.13 |
| TruthfulQA (0-shot) | 44.16 |
| Winogrande (5-shot) | 51.30 |
| GSM8k (5-shot) | 0.00 |
New Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 4.10 |
| IFEval (0-Shot) | 15.75 |
| BBH (3-Shot) | 3.17 |
| MATH Lvl 5 (4-Shot) | 0.00 |
| GPQA (0-shot) | 1.01 |
| MuSR (0-shot) | 3.17 |
| MMLU-PRO (5-shot) | 1.51 |