sarvamai/samvaad-hi-v1
Viewer • Updated • 101k • 281 • 67
How to use Tensoic/Gemma-2B-Samvaad with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="Tensoic/Gemma-2B-Samvaad") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Tensoic/Gemma-2B-Samvaad")
model = AutoModelForCausalLM.from_pretrained("Tensoic/Gemma-2B-Samvaad")How to use Tensoic/Gemma-2B-Samvaad with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Tensoic/Gemma-2B-Samvaad"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "Tensoic/Gemma-2B-Samvaad",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/Tensoic/Gemma-2B-Samvaad
How to use Tensoic/Gemma-2B-Samvaad with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "Tensoic/Gemma-2B-Samvaad" \
--host 0.0.0.0 \
--port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "Tensoic/Gemma-2B-Samvaad",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker run --gpus all \
--shm-size 32g \
-p 30000:30000 \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--env "HF_TOKEN=<secret>" \
--ipc=host \
lmsysorg/sglang:latest \
python3 -m sglang.launch_server \
--model-path "Tensoic/Gemma-2B-Samvaad" \
--host 0.0.0.0 \
--port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "Tensoic/Gemma-2B-Samvaad",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use Tensoic/Gemma-2B-Samvaad with Docker Model Runner:
docker model run hf.co/Tensoic/Gemma-2B-Samvaad
This model is a fine-tuned version of google/gemma-2b on the samvaad-hi-v1 dataset.
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 42.55 |
| AI2 Reasoning Challenge (25-Shot) | 46.59 |
| HellaSwag (10-Shot) | 68.17 |
| MMLU (5-Shot) | 33.09 |
| TruthfulQA (0-shot) | 39.95 |
| Winogrande (5-shot) | 61.64 |
| GSM8k (5-shot) | 5.84 |
The following hyperparameters were used during training:
Base model
google/gemma-2b