Instructions to use chinmaykumar-vyas/sarvam-105b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use chinmaykumar-vyas/sarvam-105b with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="chinmaykumar-vyas/sarvam-105b", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("chinmaykumar-vyas/sarvam-105b", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use chinmaykumar-vyas/sarvam-105b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "chinmaykumar-vyas/sarvam-105b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "chinmaykumar-vyas/sarvam-105b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/chinmaykumar-vyas/sarvam-105b

SGLang

How to use chinmaykumar-vyas/sarvam-105b with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "chinmaykumar-vyas/sarvam-105b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "chinmaykumar-vyas/sarvam-105b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

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 "chinmaykumar-vyas/sarvam-105b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "chinmaykumar-vyas/sarvam-105b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use chinmaykumar-vyas/sarvam-105b with Docker Model Runner:
```
docker model run hf.co/chinmaykumar-vyas/sarvam-105b
```

sarvam-105b / config.json

chinmaykumar-vyas

rahular

Duplicate from sarvamai/sarvam-105b

b29a6e1 7 months ago

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	{
	"architectures": [
	"SarvamMLAForCausalLM"
	],
	"attention_dropout": 0.0,
	"attn_implementation": null,
	"auto_map": {
	"AutoConfig": "configuration_sarvam_moe.SarvamMLAConfig",
	"AutoModel": "modeling_sarvam_moe.SarvamMLAModel",
	"AutoModelForCausalLM": "modeling_sarvam_moe.SarvamMLAForCausalLM"
	},
	"default_theta": 10000.0,
	"dtype": "float32",
	"embedding_dropout": 0.0,
	"eos_token_id": 1,
	"first_k_dense_replace": 1,
	"head_dim": 576,
	"hidden_act": "silu",
	"hidden_size": 4096,
	"initializer_range": 0.006,
	"intermediate_size": 16384,
	"kv_lora_rank": 512,
	"max_position_embeddings": 131072,
	"model_type": "sarvam_mla",
	"moe_intermediate_size": 2048,
	"moe_router_enable_expert_bias": true,
	"num_attention_heads": 64,
	"num_experts": 128,
	"num_experts_per_tok": 8,
	"num_hidden_layers": 32,
	"num_shared_experts": 1,
	"output_dropout": 0.0,
	"output_router_logits": false,
	"pad_token_id": 0,
	"q_head_dim": 192,
	"qk_nope_head_dim": 128,
	"qk_rope_head_dim": 64,
	"rms_norm_eps": 1e-06,
	"rope_scaling": {
	"beta_fast": 32,
	"beta_slow": 1,
	"factor": 40,
	"mscale": 1.0,
	"mscale_all_dim": 1.0,
	"original_max_position_embeddings": 4096,
	"type": "deepseek_yarn"
	},
	"rope_theta": 10000.0,
	"routed_scaling_factor": 2.5,
	"tie_word_embeddings": false,
	"transformers_version": "4.57.2",
	"use_cache": true,
	"use_qk_norm": true,
	"v_head_dim": 128,
	"vocab_size": 262144
	}