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| Name | Quant method | Size |
|---|---|---|
| tinyllama-1.1b-chat-v0.4.q2_k.gguf | q2_k | 482.15 MB |
| tinyllama-1.1b-chat-v0.4.q3_k_m.gguf | q3_k_m | 549.85 MB |
| tinyllama-1.1b-chat-v0.4.q4_k_m.gguf | q4_k_m | 667.82 MB |
| tinyllama-1.1b-chat-v0.4.q5_k_m.gguf | q5_k_m | 782.05 MB |
| tinyllama-1.1b-chat-v0.4.q6_k.gguf | q6_k | 903.42 MB |
| tinyllama-1.1b-chat-v0.4.q8_0.gguf | q8_0 | 1.17 GB |
from transformers import AutoTokenizer
import transformers
import torch
model = "PY007/TinyLlama-1.1B-Chat-v0.4"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
CHAT_EOS_TOKEN_ID = 32002
prompt = "How to get in a good university?"
formatted_prompt = (
f"<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n"
)
sequences = pipeline(
formatted_prompt,
do_sample=True,
top_k=50,
top_p = 0.9,
num_return_sequences=1,
repetition_penalty=1.1,
max_new_tokens=1024,
eos_token_id=CHAT_EOS_TOKEN_ID,
)
for seq in sequences:
print(f"Result: {seq['generated_text']}")